Atmospheric Composition Change: Ecosystems–Atmosphere Interactions

Atmospheric Environment 43 (2009) 5193–5267

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Atmospheric Environment

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Review Atmospheric composition change: Ecosystems–Atmosphere interactions

D. Fowler a,*, K. Pilegaard b, M.A. Sutton a, P. Ambus b, M. Raivonen c, J. Duyzer d, D. Simpson e,f, H. Fagerli f, S. Fuzzi g, J.K. Schjoerring h, C. Granier i,j,k, A. Neftel l, I.S.A. Isaksen m,n,P.Lajo,p, M. Maione q, P.S. Monks r, J. Burkhardt s, U. Daemmgen t, J. Neirynck u, E. Personne v, R. Wichink-Kruit w, K. Butterbach-Bahl x, C. Flechard y, J.P. Tuovinen z, M. Coyle a, G. Gerosa aa, B. Loubet v, N. Altimir c, L. Gruenhage ab, C. Ammann l, S. Cieslik ac, E. Paoletti ad, T.N. Mikkelsen b, H. Ro-Poulsen ae, P. Cellier v, J.N. Cape a, L. Horva´th af, F. Loreto ag,U¨ . Niinemets ah, P.I. Palmer ai, J. Rinne aj, P. Misztal a, E. Nemitz a, D. Nilsson ak, S. Pryor al, M.W. Gallagher am, T. Vesala aj, U. Skiba a, N. Bru¨ ggemann x, S. Zechmeister-Boltenstern an, J. Williams ao, C. O’Dowd ap, M.C. Facchini g, G. de Leeuw aq, A. Flossman o, N. Chaumerliac o, J.W. Erisman ar a Centre for Ecology and Hydrology, EH26 0QB Penicuik Midlothian, UK b Risø National Laboratory, Technical University of Denmark, 4000 Roskilde, Denmark c Department of Forest Ecology, University of Helsinki, 00014 Helsinki, Finland d TNO Institute of Environmental Sciences, 3584 CB Utrecht, The Netherlands e Department Radio and Space Science, Chalmers University of Technology, 41296 Gothenburg, Sweden f Norwegian Meteorological Institute, 0313 Oslo, Norway g Istituto di Scienze dell’Atmosfera e del Clima – CNR, 40129 Bologna, Italy h Royal and Veterinary and Agricultural University, 1870 Frederiksberg C, Denmark i UPMC Univ. Paris 06, LATMOS-IPSL; CNRS/INSU, LATMOS-IPSL, 75005 Paris, France j NOAA Earth System Research Laboratory, 80305-3337 Boulder, USA k Cooperative Institute for Research in Environmental Sciences, University of Colorado, 80309-0216 Boulder, USA l Agroscope FAL Reckenholz, Swiss Federal Research Station for Agroecology and Agriculture, 8046 Zurich, Switzerland m Department of Geosciences, University of Oslo, Inst. For Geologibygningen, 0371 OSLO, Norway n Center for International Climate and Environmental Research – Oslo (CICERO), 0349 Oslo, Norway o Laboratoire de Me´te´orologie Physique, Observatoire de Physique du Globe de Clermont-Ferrand, Universite´ Blaise Pascal – CNRS, 63177 Aubie`re, France p Laboratoire de Glaciologie et Ge´ophysique de l’Environnement, Observatoire des Sciences de l’Universite´ de Grenoble, Universite´ J. Fourier – CNRS, 38400 Saint Martin d’Heres, France q Universita’ di Urbino, Istituto di Scienze Chimiche ‘‘F. Bruner’’, 61029 Urbino, Italy r Department of Chemistry, University of Leicester, Leicester LE1 7RH, UK s University of Bonn, Institute of Crop Science and Resource Conservation – Plant Nutrition, 53115 Bonn, Germany t Bundesforschungsanstalt fu¨r Landwirtschaft (FAL) Institut fu¨r Agraro¨kologie, 38116 Braunschweig, Germany u Research Institute for Nature and Forest, 9500 Geraardsbergen, Belgium v INRA, INA PG, UMR Environm & Grandes Cultures, F-78850 Thiverval Grignon, France w Department of Meteorology and Air Quality, Wageningen University and Research Centre, 6700 AA Wageningen, The Netherlands x Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Forschungszentrum Karlsruhe GmbH, 82467 Garmisch-Partenkirchen, Germany y Soils, Agronomy and Spatialization (SAS) Unit INRA, 35042 Rennes, France z Finnish Meteorological Institute, 00560 Helsinki, Finland aa Dipartimento di Matematica e Fisica ‘‘Niccolo` Tartaglia’’, Universita` Cattolica del Sacro Cuore, 25121 Brescia, Italy ab Institute for Plant Ecology, Justus-Liebig-University of Giessen, 35392 Giessen, Germany ac Institute for Environment and Sustainability, The European Commission, Joint Research Centre, 21020 Ispra, Italy ad Istituto per la Protezione delle Piante – CNR, 50019 Sesto Fiorentino, Italy ae Botanical Institute, University of Copenhagen, 1353 Copenhagen K, Denmark af Hungarian Meteorological Service, 1675 Budapest, Hungary ag Istituto di Biologia Agroambientale e Forestale – CNR, 00015 Monterotondo Scalo, Italy ah Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 51014 Tartu, Estonia ai School of GeoSciences, University of Edinburgh, EH9 3JN Edinburgh, UK aj Department of Physical Sciences, University of Helsinki, 00014 Helsinki, Finland ak Department of Applied Environmental Science, Atmospher Science Unit, Stockholm University, 10691 Stockholm, Sweden al Atmospheric Science Program, Department of Geography, Indiana University, 47405-7100 Bloomington, USA am School of Earth, Atmospheric and Environmental Sciences, The University of Manchester, M13 9PL Manchester, UK

* Corresponding author. Tel.: þ44 (0) 131 445 4343; fax: þ44 (0) 131 445 3943. E-mail address: [email protected] (D. Fowler)

1352-2310/$ – see front matter Ó 2009 Published by Elsevier Ltd. doi:10.1016/j.atmosenv.2009.07.068 5194 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 an Department of Forest Ecology, Federal Research and Training Centre for Forests, Natural Hazards and Landscape, 1131 Vienna, Austria ao Max-Planck-Institut fu¨r Chemie, 55128 Mainz, Germany ap Department of Experimental Physics and Environmental Change Institute, National University of Ireland, Galway, Ireland aq Climate and Global Change Unit, Research and Development, Finnish Meteorological Institute, 00560 Helsinki, Finland ar Energy Research Centre of The Netherlands, 1755 ZG Petten, The Netherlands article info abstract

Article history: Ecosystems and the atmosphere: This review describes the state of understanding the processes involved in Received 29 January 2009 the exchange of trace gases and aerosols between the earth’s surface and the atmosphere. The gases Received in revised form covered include NO, NO2, HONO, HNO3,NH3,SO2, DMS, Biogenic VOC, O3,CH4,N2O and particles in the size 27 July 2009 range 1 nm–10 mm including organic and inorganic chemical species. The main focus of the review is on the Accepted 29 July 2009 exchange between terrestrial ecosystems, both managed and natural and the atmosphere, although some new developments in ocean–atmosphere exchange are included. The material presented is biased towards Keywords: the last decade, but includes earlier work, where more recent developments are limited or absent. Dry deposition Trace gas fluxes New methodologies and instrumentation have enabled, if not driven technical advances in measure- Resuspension ment. These developments have advanced the process understanding and upscaling of fluxes, especially Biogenic emissions for particles, VOC and NH3. Examples of these applications include mass spectrometric methods, such as Compensation points Aerosol Mass Spectrometry (AMS) adapted for field measurement of atmosphere–surface fluxes using micrometeorological methods for chemically resolved aerosols. Also briefly described are some advances in theory and techniques in micrometeorology. For some of the compounds there have been paradigm shifts in approach and application of both techniques and assessment. These include flux measurements over marine surfaces and urban areas using micrometeorological methods and the up-scaling of flux measurements using aircraft and satellite remote sensing. The application of a flux-based approach in assessment of O3 effects on vegetation at regional scales is an important policy linked development secured through improved quantification of fluxes. The coupling of monitoring, modelling and intensive flux measurement at a continental scale within the NitroEurope network represents a quantum development in the application of research teams to address the underpinning science of reactive nitrogen in the cycling between ecosystems and the atmosphere in Europe. Some important developments of the science have been applied to assist in addressing policy questions, which have been the main driver of the research agenda, while other developments in understanding have not been applied to their wider field especially in chemistry-transport models through deficiencies in obtaining appropriate data to enable application or inertia within the modelling community. The paper identifies applications, gaps and research questions that have remained intractable at least since 2000 within the specialized sections of the paper, and where possible these have been focussed on research questions for the coming decade. Ó 2009 Published by Elsevier Ltd.

Contents

1. Introduction ...... 5196 1.1. Scale...... 5197 1.2. Reactivity of natural surfaces ...... 5197 1.3. Frameworks for analysis and interpretation of trace gas and aerosol exchange ...... 5197 1.4. Bi-directional exchange ...... 5198 1.5. Aerosols ...... 5198 1.6. Ocean–atmosphere exchange ...... 5198 1.7. Wet deposition ...... 5199 2. Reactive gaseous nitrogen compounds – oxidized nitrogen ...... 5199 2.1. Introduction ...... 5199 2.2. Emissions from soils ...... 5199

2.3. Emissions of NOy from plant surfaces ...... 5201 2.4. Canopy atmosphere interactions ...... 5201 2.5. Models and measurements ...... 5201

2.6. Exchange of HNO3,HONO,PAN ...... 5202 2.7. NOx production and emission from snow surfaces ...... 5205 2.8. Up-scaling and regional and global trends ...... 5205 3. Biosphere atmosphere exchange of ammonia ...... 5205 3.1. Introduction ...... 5205 3.2. Advances in measurement methods ...... 5206 3.3. Key controls on biosphere atmosphere exchange of ammonia ...... 5208 3.4. Effects of ecosystem type on ammonia biosphere–atmosphere exchange ...... 5209 3.5. Modelling surface–atmosphere exchange of ammonia ...... 5209 3.6. Dynamic simulation of ecosystem C–N cycling and ammonia fluxes ...... 5210 3.7. Integrating ammonia exchange processes ...... 5211 3.8. Future challenges for ammonia exchange ...... 5212 4. Sulphur dioxide ...... 5212 4.1. Introduction ...... 5212 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5195

4.2. Worldwide advances in SO2 ﬂux monitoring and modelling ...... 5213 4.2.1. Asia ...... 5213 4.2.1.1. Sulphur dioxide deposition to soils ...... 5213 4.2.1.2. Micrometeorological measurements over vegetated areas ...... 5214 4.2.1.3. Long-term deposition studies and inferential modelling ...... 5214 4.2.2. North America ...... 5214 4.2.3. Europe ...... 5215 4.2.3.1. Long-term flux monitoring in the UK ...... 5215 4.2.3.2. Other recent European datasets ...... 5215 4.3. Control of surface uptake rates by leaf cuticular chemistry ...... 5216 4.4. Advances in deposition modelling ...... 5217 4.5. Future challenges ...... 5217 5. Ozone...... 5218 5.1. Introduction ...... 5218 5.2. Deposition rates ...... 5219 5.2.1. European forests ...... 5219 5.2.2. Crops ...... 5220 5.2.3. Grasslands ...... 5221 5.2.4. Other vegetated surfaces ...... 5221 5.2.5. Non-vegetated surfaces ...... 5221 5.2.5.1. Snow ...... 5221 5.2.5.2. Water ...... 5221 5.3. Non-stomatal deposition processes ...... 5222 5.4. Model development and validation ...... 5222 5.5. Risk assessment methods ...... 5223 5.6. Potential effects of climate change ...... 5224 6. Biogenic volatile organic compounds (BVOC) ...... 5225 6.1. Introduction ...... 5225 6.1.1. Volatile isoprenoids ...... 5225 6.1.2. Oxygenated volatile compounds ...... 5225 6.2. Environmental controls on BVOC emissions ...... 5225 6.2.1. Physiological and physico-chemical controls of emissions ...... 5225 6.2.2. Physico-chemical controls of emission in species lacking specific storage structures ...... 5226 6.2.3. Uptake and release of volatile compounds by vegetation ...... 5226

6.2.4. CO2-Dependence of emissions ...... 5227 6.2.5. Induced emissions ...... 5227 6.3. Contemporary difficulties in scaling BVOC emissions from leaf to ecosystem ...... 5227 6.4. BVOC fluxes over Europe, by compound and in relation to the needs of photochemical oxidant models ...... 5227 6.4.1. Flux measurement techniques ...... 5227 6.4.2. Isoprene ...... 5227 6.4.3. Monoterpenes ...... 5228 6.4.4. Sesquiterpenes ...... 5228 6.4.5. Methanol ...... 5228 6.4.6. Acetone and acetaldehyde ...... 5228 6.4.7. Other compounds ...... 5228 6.5. The EU large field campaigns in the Mediterranean area: from BEMA to ACCENT ...... 5228 6.6. Remote sensing of BVOC ...... 5229 7. Deposition and resuspension of aerosols onto and from terrestrial surfaces ...... 5230 7.1. Introduction ...... 5230 7.2. Review of new measurement approaches and instrumentation ...... 5231 7.2.1. Flux measurements of particle numbers (size-resolved or total), without information on chemical composition ...... 5231 7.2.2. Flux measurements of individual aerosol chemical species ...... 5232 7.3. Area sources of particles ...... 5232 7.3.1. Resuspension ...... 5232 7.3.2. Urban emissions of aerosols ...... 5232 7.4. Dry deposition of particles ...... 5233 7.4.1. Dry deposition rates to vegetation ...... 5233

7.4.1.1. Friction velocity (u*) ...... 5234 7.4.1.2. Surface roughness length (z0) and canopy morphology ...... 5234 7.4.1.3. Particle diameter (Dp) ...... 5235 7.4.1.4. Atmospheric stability (z ¼ 1/L)...... 5236 7.4.2. Parameterising and modelling deposition rates ...... 5236 7.4.3. Dry deposition rates to urban areas ...... 5236 7.5. Uncertainties ...... 5236 7.5.1. Uncertainties in the application of micrometeorological flux measurement techniques for deriving the local flux ...... 5236 7.5.2. Relating measured fluxes to surface exchange: flux divergence and the effect of chemical interactions ...... 5237 7.5.3. Interpretation of measurements for model verification ...... 5238 7.6. Future research needs ...... 5238 7.6.1. Deposition measurements and reporting ...... 5238 7.6.1.1. Standardisation of eddy covariance approaches and data analysis procedures ...... 5238 5196 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

7.6.1.2. Improved measurements in the accumulation mode ...... 5238 7.6.1.3. Understanding the effect of stability and leaf properties on deposition velocities ...... 5238 7.6.1.4. Filtering or accounting for chemical interactions and water uptake ...... 5239 7.6.2. Deposition models ...... 5239 7.6.2.1. Migration to a probabilistic approach ...... 5239 7.6.2.2. Improvement of modelling approaches ...... 5239 7.6.2.3. Impact of surface anisotropy on suspension & deposition ...... 5239 7.7. Conclusions – aerosols ...... 5239

8. Ecosystem–atmosphere exchange of the radiatively active gases – N2O and CH4 ...... 5240 8.1. Introduction ...... 5240

8.2. Global budgets of N2O and CH4 ...... 5240 8.3. Biological sources of N2O and CH4 ...... 5240 8.3.1. The biology of production and consumption of N2O and CH4 in soils and sediments ...... 5240 8.3.2. Distribution of active microbial populations in soils ...... 5241

8.3.3. N2O and CH4 ﬂuxes from the main global ecosystems ...... 5241 8.3.4. Plant-mediated transport and production of N2O and CH4 ...... 5241 8.3.4.1. Methane from vegetation ...... 5241 8.3.4.2. Nitrous oxide from vegetation ...... 5241

8.4. New developments in measurements of N2O and CH4 and denitriﬁcation ...... 5242 8.4.1. Flux chambers ...... 5242 8.4.2. Micrometeorological methods ...... 5242 8.4.3. Comparison of eddy covariance with chamber methods ...... 5242 8.4.4. Recent methodological advances in measurements of total denitrification rates ...... 5243

8.5. Modelling of N2O and CH4 ﬂuxes at site and regional scales: approaches, applications and uncertainties ...... 5243 8.6. Validation of models by landscape and regional scale measurements ...... 5244 8.7. Conclusions ...... 5244 9. Exchange of trace gases and aerosols over the oceans ...... 5245 9.1. New trace gas interactions at the air–sea interface ...... 5245 9.1.1. Case studies ...... 5245 9.1.1.1. Acetone (ocean uptake) ...... 5245 9.1.1.2. Methanol (ocean uptake) ...... 5246 9.1.1.3. Isoprene (ocean emission) ...... 5247 9.1.1.4. Halogenated organics (ocean emission and uptake) ...... 5247 9.1.1.5. Monoterpenes (ocean emission) ...... 5247 9.1.1.6. Alkyl nitrates (ocean emission) ...... 5247 9.2. Aerosols ...... 5247 9.2.1. Primary marine aerosol (PMA) source functions ...... 5247 9.2.2. Chemical composition of primary sea spray ...... 5248 9.2.3. Secondary aerosol production ...... 5250 10. The processes of wet scavenging of aerosols and trace gases from the atmosphere ...... 5251 10.1. Introduction ...... 5251 10.2. Nucleation scavenging of drops and ice crystals ...... 5251 10.3. Impaction scavenging of aerosol particles ...... 5251 10.4. Scavenging of gases ...... 5252 10.5. Clouds ...... 5252 10.6. Orographic precipitation ...... 5252 10.7. Organic N in air and rain ...... 5253 10.8. Conclusions and some priority areas of future research ...... 5253 11. Ecosystem–atmosphere exchange – concluding remarks ...... 5254 11.1. Policy needs ...... 5254 11.2. Current understanding ...... 5254 11.3. Future developments ...... 5254 Acknowledgements ...... 5255 References ...... 5255

1. Introduction exchange processes is a core activity in understanding the Earth system. The subject of this review is much narrower than the The composition of the earth’s atmosphere is unique in the scope of these opening lines, and is restricted to the trace gases solar system in being largely determined by biological processes and aerosols exchanged between the atmosphere and the earth’s in soils, vegetation and the oceans interacting with physical and surface. However, as is clear from much of the international chemical processes within the atmosphere. The physical surface– assessment of changes in atmospheric composition since the atmosphere exchange of most gases contributing major and trace industrial revolution, these trace atmospheric constituents are constituents of the atmosphere is coupled to biological produc- changing the earth’s climate (IPCC, 2007), global biodiversity tion processes and transferred through the surface–atmosphere (Millenium Ecosystem Assessment, 2005) and the biogeochemical interface. Thus, developing a mechanistic understanding of the cycling of major nutrients including nitrogen, carbon, and production and destruction processes and their interactions with sulphur. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5197

The earth’s surface is a sink for some atmospheric trace gases the photochemical oxidants in the 1960s and 1970s (Husar et al., and aerosols, and a source for many others, and for most the 1978). These early studies were made to determine the importance of surface–atmosphere interface represents a zone within which most surface removal which is better known as dry deposition (to distin- of the overall control of fluxes occurs. An understanding of the rate guish the process from removal by precipitation) as a sink for reactive controlling processes at this interface is therefore vital in describing trace gases (NO2,SO2,O3). Advances in understanding and computing the exchange process and understanding the global biogeochemical resources have allowed more sophisticated approaches to be adop- cycles. Applications of science in this field are necessary to quantify ted, in which the processes at the surface recognised different sinks and model responses to human perturbation of many of the and interactions with other trace gases, allowing rates of dry depo- biogeochemical cycles (C, N, S, halogens and metals to name but sition to change with time and with surface characteristics. a few). These perturbations include changes in land use or emissions of trace gases to the atmosphere, through combustion and 1.1. Scale industrial activities. Taking as an example the global nitrogen cycle, human activity through combustion processes for oxidized nitrogen Emission or deposition schemes to quantify trace gas fluxes and the Haber Bosch process for reduced nitrogen now dominates operate at a range of scales depending on the applications, illustrated the cycling of reactive nitrogen through the atmosphere and back to in Fig. 1.1. For hourly integration the application is primarily terrestrial and marine ecosystems (Galloway et al., 2004). The total for research purposes and mechanistic study at the small scale 2 2 emission of reactive nitrogen (Nr) from human activities at the end (<10 m ). For landscape scale measurements and for assessment of of the 20th century exceeds that from natural processes by a factor the fate of pollutants at the regional scale (106 km2) the application of 4 (20.7 Tg of oxidized and reduced reactive nitrogen Nr from has both research and policy objectives. At this scale, spatial and natural sources within a total of 104 Tg-N in 1993, Galloway et al., temporal integration provides robust parameterisation. The appli- 2004). As nitrogen is a limiting nutrient in many ecosystems, cation in global models to quantify sources and sinks is restricted in these modifications of the natural cycling have profound effects on spatial resolution, typically to 1 1, and likewise has research and ecosystem function, biodiversity and atmospheric composition policy application Dentener et al., 2006. For the landscape scale, flux (Erisman et al., 2008). The human disturbance of the global carbon measurements may be made directly, using micrometeorological cycle is also extensive, and the quantities involved are very large. methods above canopies of vegetation, soil, or even ocean surfaces Global emissions of CO2 from fossil fuels since 1700 amount to and have become the method of choice for long-term flux approximately 600 Gt-C, which have increased the atmospheric CO2 measurement. These techniques provide, in addition to the target mixing ratio from 280 ppm to 380 ppm in 2006, an increase of about trace gas flux the turbulent exchange characteristics of the under- 30%, (IPCC, 2007). lying surface and the partitioning of available radient energy which These high level indicators of human influence provide essential enables the processes to be investigated at a sufficiently large scale to context for this review paper, but conceal the detailed changes integrate canopy scale fluxes over typically 105 m2 (Baldocchi et al., taking place and the range of chemical species and interactions 2001). involved. The subject area includes many different chemical species, The sections focus mainly on individual trace gases or classes of and it is not possible to be comprehensive in this review for all gases. atmospheric particles, and each considers the surface–atmosphere In particular the subject of the global carbon cycle and CO2 in exchange over specific ecosystems. The exceptions are the ocean particular are much too large to cover in this review. The focus of this surfaces and wet deposition, within which a range of relevant review is on the reactive trace gases and for the greenhouse gases, compounds is considered. CH4 and N2O. The gases are associated with a range of biological sources and have varied chemical reactivity in the atmosphere and at 1.2. Reactivity of natural surfaces surfaces. These differences reveal the range of controls and temporal and spatial variability in rates of exchange, which are the focus of the For many of the short lived gases (<2 days in the boundary review. The review moves through a range of chemical species, layer) there are multiple sinks at the surface and these include identifying the current state of knowledge and, where possible foliar surfaces and soil whose properties as sinks for a range of applications of the new developments in a policy context. gases vary with humidity and the presence of surface water and The gases emitted from terrestrial and ocean ecosystems are influenced, sometimes strongly, by the presence of other gases include all of the major greenhouse gases, H2O, CO2,CH4 and N2O, (Fig. 1.2). The chemical and physical complexity of terrestrial the nitrogen gases (both in reduced and oxidized forms), sulphur surfaces, illustrated in Figs. 1.1 and 1.2 at the microscopic scale is compounds, volatile organic compounds (VOC) and halogens. greatly simplified in the parameterisations used in models. The Quantifying the fluxes of these trace atmospheric components is simplification is necessary in part due to the nature of the flux a prerequisite within an assessmemnt process leading to the devel- measuring systems, which integrate the net fluxes over large areas opment of policy on climate change, eutrophication, acidification of these surfaces, and fail to reveal the microscopic scale of and photochemical oxidant formation. Many research groups have variability of the true exchange. become involved in the measurement and modelling of emission and uptake (deposition) fluxes of trace gases and particles. The mecha- 1.3. Frameworks for analysis and interpretation nistic understanding has developed from two different fields of of trace gas and aerosol exchange study, the first was concerned with the sources of atmospheric trace constitiuents, and the greenhouse gases were among the first The measurements of surface–atmosphere exchange provide at compounds for which surface fluxes were quantified directly by the simplest level the mass exchange per unit area of surface, which field measurements. These included small scale (0.1 m–0.5 m2) may be ground, water or leaf area, per unit time. To extract useful measurements of fluxes from soils and vegetation using chamber information on the underlying processes it is necessary to quantify methods for CO2, CO, CH4,N2O(Junge, 1963). The measurements the contributions each step in the transfer pathway makes to the showed large spatial and temporal variability so that up-scaling to overall exchange between defined points, which in this scheme is regions generated very large uncertainties. The other development simplified to vertical levels between a source and a sink. The most was mainly associated with the atmospheric transport and deposi- widely applied transfer scheme is a resistance analogue (Monteith tion of pollutants, including nitrogen and sulphur compounds and and Unsworth, 2007), in which the flux of trace gas or particle 5198 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

Fig. 1.1. A diagrammatic representation of the scales of measurement of trace gas fluxes for process studies (a transverse section through a Phaseolus vulgaris leaf, showing the palisade and mesophyll cells bounded by epidermal cells and the airspaces for internal exchange between trace gases and intercellular fluid). The field scale at which most of the micrometeorological flux measurements are made and the continental scale where models provide the emission and deposition fluxes. In this case the emission fluxes of oxides of nitrogen over Europe are shown, revealing the importance of international shipping to emissions over continental scales. is treated as an analogue of electrical current flowing through 1.4. Bi-directional exchange a simple network of resistances, which may act in series if there is just one sink at the surface, such as a pure water surface, or may For many of the trace gases, regardless of their reactivity, the have several sinks at the surface, acting in parallel, each repre- exchange fluxes may vary in sign as well as magnitude, with senting a distinct chemical component of the underlying surface. emission and deposition being commonly observed. The most A simple resistance network representing three different sinks widely known example of bi-directional exchange is CO2, which at the surface, and the two atmospheric resistances (Ra and exhibits both deposition and emission fluxes due to photosynthesis Rb, respectively the turbulent transfer resistance and the leaf and respiration respectively. In this case the concept of compen- boundary-layer resistance) are illustrated in Fig. 1.3. sation points as mixing ratios at which no net exchange takes place The atmospheric resistances may be separated from the total is now widely recognised for a range of trace gases (NH3, NO, CO2) resistance using independent measures of the turbulence above the but all controlled by very different processes. vegetation. The overall flux may be measured by a variety of micro- The recognition of bi-directional exchange requires modelling meteorological methods (Monteith and Unsworth, 2007), and thus approaches to simulate the process for application in surface– the total of the surface or canopy resistances to transfer between the atmosphere exchange schemes, as illustrated for NH3 in Fig. 1.4. source and sink may be quantified as the residual, as shown in Fig.1.3. 1.5. Aerosols

The understanding of deposition and emissions of aerosols over terrestrial surfaces has advanced considerably in the last decade, after a long period in which application of a model developed by Slinn (1982) has been a standard for many modelling approaches. Likewise, the emission of aerosols by resuspension from terrestrial surfaces has advanced following innovative new measurement approaches described in this review.

1.6. Ocean–atmosphere exchange

For many years the ocean–atmosphere exchange of trace gases has been treated in a simplistic way (Liss et al., 1981), in part due to the relative simplicity of the ocean surface relative to terrestrial surfaces, but also due to the limited knowledge base to support more complex treatments. However there has been an accelerating interest in ocean– Fig. 1.2. Illustrating the importance of different sinks for reaction of trace gases at the atmosphere exchange as new techniques have become available terrestrial surfaces, notably the external surfaces of vegetation often as in this case to make the flux measurements and as very new issues have been covered by complex layers of epicuticular wax and illustrated in Fig. 1.1, the internal structure of leaves, following uptake through the stomatal apertures and soils greatly identified. Current interest in oceanacidificationandoceaneutro- simplified in this illustration. phication further raise the profile of ocean–atmosphere exchange, and D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5199

deposition footprint of pollutants (e.g. with reference to acidiﬁcation, χ O3(z-d) eutrophication, metal deposition or photochemical oxidants). These Ra applications require an understanding of the fate and transformations of the emitted trace gases within the atmosphere. The developments

RbO3 in understanding atmospheric chemistry of the trace gases discussed R ++= RRR in this paper are reviewed in the companion paper (Monks et al., this F t cba O3 issue)inthisvolume. R c2 1 R cuticle R R = c3 c1 c 1 1 1 2. Reactive gaseous nitrogen compounds – oxidized nitrogen soil stomata ++ Rc1 Rc2 Rc3 2.1. Introduction

χ ' O3(z 0 )= 0 Developments in understanding surface–atmosphere exchanges of NO and NO2 over the last decade have focussed on three specific issues: the long-term emission of NO from soils; the interaction of Fig. 1.3. A simple resistance analogy for a trace gas with sinks in stomata, on foliar chemical processing of nitrogen oxides in and above plant canopies; surfaces and in soil. and the deposition of NO2 and HNO3 to foliar and soil surfaces. The measurements have been made over different vegetation, but the given that these surfaces cover 71% of the earth’s surface, the relatively recent focus has been on forests, in part because the interactions small section of this review paper on this topic belies its importance in between these processes are greatest for forests, but also because understanding atmospheric composition change. some of the measurements are simpler to make and interpret for mature forests. This section outlines the developments in under- 1.7. Wet deposition standing NOy exchange between terrestrial ecosystems and the atmosphere, concentrating on developments during the last decade. Process understanding in the scavenging of gases and particles by precipitation has continued to advance, with important devel- 2.2. Emissions from soils opments during the last decade. The applications of wet deposition schemes are very important in the Long-Range Transport (LRT) Soil surface emissions of NO are the result of several biological models and increasingly in global chemistry-transport models and abiotic processes in the soil producing and consuming NO. (CTM) (Stevenson et al., 2006). These two applications make very Production and consumption of NO occurs predominantly via the different demands on available knowledge and understanding. In biological nitrification and denitrification processes. Nitrification is þ the case of LRT models in Europe (e.g. EMEP), the applications the oxidation of soil NH4 to NO3 , and denitrification is the anaerobic form part of the integrated assessment process and within the user reduction of soil NO3 to N2O and N2. In nitrification, NO is formed as þ community the pressure to provide ever finer spatial scale esti- a by-product during the oxidation of NH4 to NO2 and possibly also as mates of inputs presents challenges in the capability of LRT models a result of nitrifier reduction of NO2 leading to an NO production of þ and the meteorological models on which they depend. Current 1–4% of the NH4 being oxidized (Skiba et al.,1997). The NO produced demand for assessments of effects at the 1 km 1 km scale allows may be transformed within the soil profile by oxidation to NO3 or it the scale of the input estimate to approach the scale of an individual may be released to the atmosphere following diffusion to the nature reserve, for example. soil surface. In denitrification, NO occurs as an intermediate in the The focus of this paper on surface–atmosphere exchange processes cascade of reductive processes, and in the soil profile NO reduction spans a wide range of trace gases and particles. The motives for studies may contribute to the formation of N2O. Abiotic production of of many of the specific gases were environmental policy related, for NO occurs from oxidation of nitrous acid (HONO) that has been example to determine the atmospheric lifetime, travel distance and produced by protonation of biologically formed NO2 (Venterea et al.,

Fig. 1.4. A diagrammatic representation of bi-directional exchange, for NH3 exchange between the atmosphere and vegetation. 5200 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

2005). Under certain conditions e.g. after application of anhydrous ammonia to agricultural soils or acidic forest soils, the coupled biological-abiotic production of NO may constitute the dominant process for soil NO emissions (Venterea and Rolston, 2000; Go¨dde and Conrad, 1998). Factors that increase nitrification and denitrification, e.g. substrate and O2 availability, temperature and pH are thus predicted to influence NO formation. Likewise, factors affecting transport processes in the soil are predicted to regulate emissions of NO (and other gases). It has been hypothesized (Davidson,1991)that where WFPS (water-filled pore space) is less than 0.6, nitrification is the dominant process and relatively high emissions of NO may be observed. Under more reducing conditions, 0.6 < WFPS < 0.9, denitrification dominates which has a higher potential for NO production compared to nitrification (Skiba et al., 1997); however under conditions where anoxic conditions are generated by high soil water content or by compaction of fine textured soil the probability of NO being re-consumed by the denitrifying community is greatly enhanced. Soil water may also play a central role in mediating chemical processes leading to NO formation (Venterea et al., 2005). Under most soil conditions, both nitrification and denitrification occur simultaneously and the net flux of NO between soil and atmosphere is the result of both processes together. As current views of controls over NO gas emissions are still incomplete and need revision e.g. with emphasis on the role of abiotic formation (Venterea et al., 2005) there is a continuous need to further develop and improve methodologies to identify and characterise the NO formation processes. Go¨dde and Conrad (1998) achieved this by a combined modelling and experimental approach to determine the net NO flux in relation to NO concentration to quantify production and consumption rate constants and compensation concentration. Recent advances in methodological approaches to deepen our understanding of soil based NO emissions have included application of stable isotope techniques. Stark et al. (2002) applied a 15N-isotope pool dilution method- to obtain the simultaneous gross rates of NO forming processes combined with soil emissions, and Russow et al. (2000) adopted a kinetic isotope method (KIM) to study the complex N transformation processes involved in soil NO emissions. Fig. 2.1. Left: NO emission (mgNm2 h1) as a function of nitrogen deposition NO and N2O emissions were measured continuously at 15 forest (g N m2 s1). Regression lines (solid ¼ significant, dashed ¼ non significant) for 2 1 sites in Europe (Pilegaard et al., 2006) including coniferous and coniferous and deciduous sites, respectively. Right: N2O emission (mgNm h )as deciduous forests in different European climates, ranging from a function of C/N ratio. The full line represents a linear regression and the dotted line boreal to temperate continental forests and from Atlantic to Medi- a logarithmic regression. terranean forests. Furthermore the sites differ in atmospheric N- deposition ranging from low deposition (0.2 g N m2 yr1) to high 2 1 deposition (4 g N m yr ). rate of O2 supply and thereby controls whether aerobic processes The relationships of the emissions of NO and N2O, with the such as nitrification or anaerobic processes such as denitrification parameters, nitrogen deposition, forest type, age, C/N in the surface dominate within the soil. While N2O emissions are known to horizon, pH, soil temperature and water-filled pore space (WFPS) increase at higher water contents through larger losses from were investigated by means of stepwise multiple regression anal- denitrification the relationship between the NO flux and the soil ysis. NO emission was dependent on forest type and positively water is more complex. Due to limited substrate diffusion at very correlated with nitrogen deposition (Fig. 2.1). WFPS was tested for low water content and limited gas diffusion at high water content, curvature by including a quadratic term, but this was not signifi- nitric oxide emissions are suspected to have a maximum at low to cant. Separately performed regression analyses for deciduous and medium soil water content. coniferous forests showed that the relationship between nitrogen The effects of soil moisture and temperature on NO and N2O deposition and NO emission was only significant for the coniferous emission were studied in laboratory experiment with soil cores forests: (NO (mgNm2 h1) ¼ 13.9 þ 25.5 [N deposition from a range of field sites (Schindlbacher et al., 2004). Soil moisture 2 1 2 (mgNm h )], r ¼ 0.82). The N2O emission was significantly and temperature explained most of the variability in NO emission negatively correlated with both the C/N ratio and the age of the (up to 74%) and N2O (up to 86%) emissions for individual soils. NO stands; a logarithmic transformation of N2O emission improved the and N2O were emitted from all soils except from a boreal pine forest significance of the correlation. soil in Finland, where the laboratory experiment showed net NO Soil temperature is a key variable affecting the emission rates of consumption. NO emissions from a German spruce forest ranged both gases (Fig. 2.2). Emissions of both NO (Slemr and Seiler, 1984) from 1.3 to over 600 mg NO–N m2 h1 and greatly exceeded and N2O(Skiba, 1998) increase with soil temperature due to the emissions from other soils. Average N2O emissions from this soil 2 1 positive effect of temperature on enzymic processes as long as tended also to be largest (170 40 mgN2O–N m h ), but did not other factors (e.g. substrate or moisture) are not limiting. Soil water differ significantly from other soils. NO and N2O emissions showed þ acts as a transport medium for NO3 and NH4 and influences the a positive exponential relationship with soil temperature. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5201

400 In general, relationships between nitrogen oxides emission and soil moisture and soil temperature can be found within a single locality when studying short-term variations. However, when comparing ]

-1 annual values from different localities within a large region, parame- h 300 -2 terisations differ appreciably between locations and other factors such as soil properties, stand age, and site hydrological conditions interfere. This scale of variability has slowed the development of improved soil NO emission inventories, and their application in global chemistry- 200 transport models. So while it is disappointing to observe current generation CTMs using 1995 soil NO estimates, it is understandable and identiﬁes a need for better parameterisations and soil emission 100 databases for global application.

2.3. Emissions of NO from plant surfaces NO emission [ μ g NO-N m y

0 Production of NOy on Scots pine branch surfaces by ultraviolet -5 0 5 10 15 20 radiation has been observed in Hyytia¨la¨, southern Finland (Hari Forest floor temperature [°C] et al., 2003)(Fig. 2.4). Other studies have shown that irradiance- dependent NOy emissions from snow and different chamber surfaces Fig. 2.2. Relationship between daily mean forest floor temperature and daily mean NO have been observed to originate from HNO3 or nitrate photolysis. In emissions at the Ho¨glwald Forest (spruce, control) for the observation period January 1, Hyytia¨la¨ forest, Raivonen et al. (2006) investigated whether the NOy 2004–December 31, 2006. For details on measurement and site characteristics see Gasche and Papen (1999). emitted from pine shoots could originate from photolysis of HNO3 attached to the needle surface. Field data of several years from Hyytia¨la¨ were used to test this hypothesis. The HNO3 deposition, estimated for the Hyytia¨la¨ site, has been high enough to account for The results from the annual averages of field data did not show the NOy emission rates observed from the chambers. The particular significant relationships with soil temperature for either NO or for characteristics of the daily pattern of CO2 exchange or stomatal N2O emission. Schindlbacher et al. (2004) showed that N2O emis- control was not reflected in the NOy flux. When a pine branch sions increased with increasing WFPS or decreasing water tension, was rinsed, which reduced the amount of water-soluble nitrogen respectively. Maximum N2O emissions were measured between 80 compounds (e.g. HNO3, nitrates and HONO) from the needle surface, and 95% WFPS or 0 kPa water tension. The optimal moisture for NOy emissions from that branch decreased compared to another NO emission differed significantly between the soils, and ranged non-rinsed branch. Therefore, it was concluded that the results between 15% WFPS in sandy Italian floodplain soil and 65% in loamy support the hypothesis and that HNO3 photolysis on plant surfaces Austrian beech forest soils. For the field data WFPS was not needs to be taken into account both from air chemistry and plant a significant parameter for N2O emission, but had a positive signif- sciences point of view. icant effect on NO emission (Fig. 2.3). The annual average WFPS in the field was higher than the optima found for NO in the laboratory 2.4. Canopy atmosphere interactions experiment, but since not all field sites were studied in the laboratory it is difficult to provide a general conclusion. The inter-annual The interaction between chemical reactions of nitrogen oxides variation within single sites clearly showed relationships to both taking place in the canopy and trunk space of a forest is a special temperature and soil moisture. An important factor for N2O emis- case because in this area chemical and turbulent timescales change sion is freeze-thaw events which can produce a significant outburst substantially leading to a very complex situation in which even the of N2O(Kitzler et al., 2006). direction of fluxes may change (Duyzer et al., 1995)(Fig. 2.5). This makes it nearly impossible to interpret measurements of the turbulent fluxes of some reactive trace species above the canopy from single point eddy covariance measurements. Several models have been Sandy loam developed to simulate the overall exchange and show the magnitudes Silty loam of the different competing processes. These models describe the Sandy clay loam Loam(1) coupled processes of atmospheric transport and chemical processes Loam(2) above and in canopies in detail. Over forests the situation is even more complex. Flux measurements are usually carried out near the top of rough canopies leading to potential inaccuracies in the K-theory approximation. This theory is relatively easy to combine with vertical atmospheric transport phenomena with fast chemical reactions.

2.5. Models and measurements

Measurementsof small ﬂuxes of NO and NO2 have shown spurious NO emission (% of maximum) results especially at low concentrations due to a lack of speciﬁcity of

0 20406080100 monitors and a lack of instrument sensitivity, but other problems may well have contributed, including violation of conditions under which 020406080100 such ﬂuxes may be measured above canopies and the complexity of WFPS(%) interactions; soils and sunlight driven reactions may both be sources Fig. 2.3. The relationship between NO emission and water-ﬁlled pore space at different of NOy and these interact with the stomatal sinks and the chemical localities in the NOFRETE project (based on data in Schindlbacher et al., 2004). processing within the canopy trunk space Duyzer et al., 1983. 5202 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

Fig. 2.4. Effect of UV radiation on the NOy concentration in a small Teﬂon chamber that enclosed a clean pine branch or a branch that had been treated with NH4NO3 solution. The branches were dead and dry, cut from the tree. UV wavelengths were ﬁltered away using a Plexiglas plate (Raivonen et al., 2006).

As a result of these limitations there are only limited data a compensation point above which the flux is directed towards the available for verification of models. Duyzer et al. (2004) described surface and below which the flux is away from the surface. the analyses of a dataset acquired in the framework of a European In summary the flux of NO2 above a forest can be described with project from an experiment carried out in a 20 m high coniferous the following function: forest (Speulderbos, The Netherlands). A 1D multi-layer model of a forest canopy was used to analyse the field data. In each layer 1 FNO2 ¼ f FNO;soil CNO2 vertical transport was described using K-theory; canopy uptake Rc;NO2 was described using a resistance layer model. Simple chemical where all variables have their common meaning and C denotes reactions between ozone and nitric oxide and photolysis of NO2 the concentration of nitrogen dioxide above the canopy. This nitrogen dioxide were described. The coupled differential equa- equation is rather qualitative but indicates the sensitivity of the flux tions were solved numerically. Input to the model calculations were of NO above the canopy. More quantitative model runs are needed, concentrations of nitrogen oxides and ozone at the highest level 2 but these require a large amount of input data and the results are above the forest, levels of radiation, temperature, humidity, wind still uncertain. speed, turbulence parameters and an estimate of the emission of nitric oxide. Output of the model is the concentration and fluxes of A simple resistance model (Duyzer et al., 2005a,b) was tested in the relevant components at the height of each level in and above a deciduous forest (Sorø, Denmark) and is illustrated in Fig. 2.6. the canopy. These may be compared with measured fluxes of these Generally the understanding of the various processes and their components at two levels above and one below the canopy. It is fair interaction is increasing. Nevertheless many uncertainties to say that the comparison between measured and modelled fluxes remain and there is a need for further improvement of models, is not impressive. There are many possible explanations for this especially for Lagrangian models incorporating chemical reac- observation but no clear single cause has been identified. tions. On the other hand, the accuracy of the results of field Depending on the magnitude of this soil flux the NO2 flux is measurements has been rather low. It should be noted that either downward or upward. In the case of the coniferous forest although the interaction between atmospheric chemical reac- described here and the conditions during the experiment the result tions and exchange between the canopy and the atmosphere is was that when the NO flux from the soil exceeded 10 ng m2 s1, easy to understand its importance may be limited. In cases where the NO2 emission was upward (i.e. away from the forest). fluxes of nitrogen oxides are small the corrections could be large At high concentrations the NO2 flux is directed towards the in a relative sense but still rather small in an absolute sense. The forest and at small concentrations the flux is more likely to be currently available models could very well be capable of making directed towards the free atmosphere. This may be interpreted as estimates of the magnitude of these effects. In view of all the uncertainties hindering improved estimates in testing of models the limited quality of the description of atmospheric transport processes within the canopy may not be a serious problem here.

2.6. Exchange of HNO3, HONO, PAN

The deposition of HNO3 to terrestrial surfaces has been shown to be primarily controlled by the rates of turbulent exchange in the atmospheric boundary layer and the leaf boundary layer (Huebert and Robert, 1985). The highly reactive and soluble nature of gaseous HNO3 leads to large rates of deposition, approaching the maximum rates of deposition limited by turbulent exchange when each molecule arriving at terrestrial surfaces is immediately absorbed at the surface. In these conditions the surface is considered to be acting as a perfect sink, canopy resistance is zero and the numerical value for the deposition velocity becomes:

Fig. 2.5. A schematic of the various canopy interactions involved in the exchange of V ¼ V ¼ 1=r þ r nitrogen oxides between the free atmosphere and forests. gðNHO3Þ max a b D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5203

Fig. 2.6. Proﬁles of CO2,NO2,O3 and NO in a beech forest near Sorø, Denmark. The proﬁles clearly show the effects of stable conditions during night and daytime turbulence mixing the full air column. CO2 is built up during night due to soil respiration; O3 is depleted during night due to deposition and chemical reactions. At the soil surface high concentrations of NO are seen due to emission from the soil.

The values for deposition velocity in these conditions are very US pine forests at Duke Forest, North Carolina, (RH > 75%) and sensitive to wind velocity values and approach several cm s1 even Blodgett Forest, California, (RH < 30%) (Farmer et al., 2006; Turn- over relatively short vegetation. The consequence of these large rates ipseed et al., 2006; Wolfe et al., 2008). of deposition are that even in areas with small HNO3 concentrations, At Duke Forest fluxes of PAN, PPN and MPAN were measured with dry deposition contributes a substantial quantity if nitrogen. Taking an a CIMS technique (Turnipseed et al., 2006). There were no significant ambient concentration of 0.1 ppb HNO3, the annual deposition of N for differences in the Vd of the three different PAN compounds, but all 1 a forest would be of the order 3 kg N ha annually from HNO3 alone. three species deposited about four times faster than predicted by the The close coupling between rates of turbulent exchange and model of Wesely (1989) during the day, and nearly an order of dry deposition rates for HNO3 also generates substantial spatial magnitude faster during the night, indicating that aqueous solubility variability in N deposition in the landscape, with hotspots for N considerations are insufficient to predict the behaviour of PAN on 1 1 deposition being forests and especially forest edges, hedgerows and surfaces. The average Vd was 2.5 mm s during day and 8 mm s isolated, exposed hills, where wind speeds are larger. during night. In contrast to the considerations of Wesely (1989),wet Several studies have recently attempted to measure total surfaces showed a smaller non-stomatal resistance (Rns ¼ 125 s m1) 1 oxidized nitrogen (NOy) fluxes or even total reactive nitrogen than dry surfaces (Rns ¼ 250 s m ). (Nr ¼ NOy þ NHx) to ecosystems (Turnipseed et al., 2006). These At the much drier Blodgett forest site, the flux of the sum of all approaches offer the prospect to apply eddy covariance techniques PANs was measured by TD-LIF, based on thermal conversion and NO2 for the robust and relatively cost effective determination of total detection (Farmer et al., 2006). PAN was derived as the difference atmospheric N deposition, but they do not provide the chemical between the ambient temperature and 180 C channel. They found speciation needed to further process understanding. There have, upward fluxes in summer and on average bi-directional exchange however, also been advances in the understanding of individual N with afternoon deposition in winter, when noon-time deposition 1 compounds other than NH3, NO and NO2. velocities averaged 8 mm s . More recently, these measurements A recent lab study (Sparks et al., 2003) has confirmed that PAN have been repeated with the more selective CIMS technique (Wolfe deposition through the stomata can make a significant contribution et al., 2008). Here measurements indicated larger average midday 1 to plant uptake of atmospheric N. In addition, recent instrument values of Vd for PPN (12 mm s ) than for the PAN and MPAN developments in chemical ionisation mass spectroscopy (CIMS) (4 mm s1), while both compounds deposited slowly at night 1 and thermal-dissociation laser induced fluorescence (TD-LIF) have (Vd < 2mms ). The authors of this study attribute the difference in enabled the application of eddy covariance to the biosphere/ the Vd between compounds to MPAN and PAN production inside the atmosphere exchange of preoxy acyl nitrates (PANs such as PAN, canopy and suggest that the PPN fluxes are a better descriptor of the PPN and MPAN). Measurements were made over two contrasting surface deposition. They suggest that the non-stomatal uptake is 5204 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 dominated, but not fully explained, by thermochemical decompo- governed by the thermodynamic equilibrium with NH4NO3 on leaf sition, and thus strongly linked to canopy temperature. surfaces or fertilizer pellets. Fig. 2.7 shows an example of reduced In summary, this recent measurement evidence suggests that deposition of HNO3 and HCl over a Dutch heathland. deposition rates of PANs in warm climates are at least a factor of 5 The view that HNO3 normally deposits with a near zero canopy larger than predicted by commonly used models and non-stomatal resistance still holds. There is an increasing measurement database deposition is larger to wet and humid surfaces than to dry surfaces. of HNO3 concentrations in national and regional networks suitable During the same TD-LIF study, Farmer et al. (2006) measured for inferential modelling of HNO3 deposition (Tang et al., 2009), fluxes of total alkyl nitrates (gas and aerosol phase), from the differ- which now provides independent confirmation from the model ence between the 180 Cand330 C channels. These compounds results, that HNO3 deposition makes a very significant contribution showed large winter-time midday deposition velocities of 20 mm s1, to nitrogen deposition across Europe. In addition, Europe-wide 1 1 approaching those of HNO3 (25 mm s ). Even higher Vd of 30 mm s monitoring activities have produced the first hourly monitoring was derived by Horii et al. (2005) for what they interpret as isoprene- datasets of HNO3, which allows for a much more in-depth assess- derived hydroxyalkyl nitrates. ment of the performance of oxidized nitrate chemistry in atmo- Nitric acid (HNO3) has traditionally been believed to deposit at spheric transport models (Tarrason and Nyiri, 2008). the maximum rate possible according to turbulence (Vmax) and its Much development has occurred in measurement techniques flux measurement continues to be used to derive quasi-laminar for nitrous acid (HONO), e.g. based on long path absorption boundary-layer resistances for vegetation (e.g. Pryor and Klemm, photometry (LOPAP) and differential optical absorption spectrom- 2004). This view has been challenged by recent measurements etry (DOAS). This has contributed to the improvement of process that indicated non-negligible canopy resistances in the range of 50 understanding of sources of HONO in the atmosphere, e.g. revealing to >200 s m1 during midday (Nemitz et al., 2004b, 2008). This larger daytime sources than previously thought and identifying has been attributed to non-zero chemical compensation points NO2 reactions with humic acid as a novel production mechanism

] 0 -1 s

-2 -10

-20 HNO3 HCl [ng m [ng χ

F -30

-40 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 30 V 25 max(HNO3) ]

-1 V 20 max(HCl) V (HNO ) 15 d 3 V d(HCl) [ mm s [ mm 10 d V 5 0 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 500

400 ] -1 300 HNO

[s m 3

c 200 R HCl 100

0 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 0.5 120 RH u 100 0.4 *

] 80 -1 0.3 ') [%] 60 0 z ( [m s [m

* 0.2

u 40 RH 0.1 20 0.0 0 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00 GMT

Fig. 2.7. A time series of HNO3 and HCl exchange measured above a Dutch heathland with a denuder gradient system with online analysis by ion chromatography. The panels show: (a) ﬂuxes, (b) deposition velocities of HNO3 and HCl in comparison with their maximum values and (c) Rc for HNO3 and HCl, (d) friction velocity (u*) and relative humidity (h). Data represent 2.5 h running means of 30 min. Vd(HNO3) and Vd(HCl) are reduced compared with their maximum values, presumably due to non-zero chemical compensation points þ originating from deposited NH4 salts. From Nemitz et al. (2004a). D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5205

(Kleffmann et al., 2005; Stemmler et al., 2006). By contrast, appli- based on intensity of rainfall) to estimate soil NO emissions. cations of these approaches to flux gradient measurements are still Yienger and Levy also provide a canopy reduction factor to include rare, which nevertheless confirm surface sources of HONO (Vitel estimates of the chemical conversion and re-deposition of NO as et al., 2002; Kleffmann et al., 2003). NO2 within the canopy. Compared to the methodology by Yienger and Levy, the Skiba-EMEP/CORINAIR approach is more simplistic. 2.7. NOx production and emission from snow surfaces Based on a literature review by Skiba et al. (1997) this approach postulates that 0.3% of any form of nitrogen is volatilized as NO, i.e. Snow lying on the Earth’s surface has traditionally been viewed regardless whether it originates from inorganic or organic fertil- as a chemically inert medium, whose influence on the overlying ization or atmospheric N deposition. Furthermore, a background atmosphere was exerted through its albedo effect, and by emission of 0.1 ng NO–N m2 s1 (z0.032 kg NO–N ha1 a1)was restricting exchange of gases between the air and land/sea surfaces. assumed (Simpson et al., 1999). In addition, EMEP/CORINAIR also The a priori view was that the boundary layer and troposphere over use a more detailed methodology (BEIS-2), which originates from Antarctica would be somewhat uninteresting, with low concen- the work of Novak and Pierce (1993) and considers soil temperature trations of reactive radicals such as OH, HO2, NO and NO2, and as well as different land use classes. A statistical summary model a composition dominated by longer-lived chemical species. The was developed by Stehfest and Bouwman (2006), which is based equivalent regions of the Arctic atmosphere were assumed domi- on the most extensive literature review currently available. nated by long-range transport of anthropogenic emissions from This methodology for calculating soil NO emissions on global and lower latitudes. However, recent research has shown that this regional scales considers land-use, N fertilization rate [Fertilizer], picture is far from the truth, and that snow is a highly photo- soil N content (three different classes, estimated as 1:10 of soil chemically active medium. Snow-pack impurities, of which there organic carbon content) [SON] and climatic regions. The method- are many, can be photolysed to release reactive trace gases to the ology was recently adapted to calculate a European wide inventory atmosphere. These processes are likely to be active anywhere that of NO emissions from forest soils (Kesik et al., 2006). Kesik et al. sunlight irradiates snow. The importance of these processes to used the process-oriented ecosystem model Forest-DNDC. The boundary layer composition varies with geographical location; in model was extensively tested for its performance to predict NO regions with a high background of radicals, for example arising emissions at the various NOFRETETE field sites, which were located from anthropogenic pollution, emissions from snow are of lesser across Europe and, thus, were covering different climatic condi- importance. But in the remote polar regions, emissions from snow tions (Pilegaard et al., 2006). Regionalisation was finally achieved can be the dominant source of reactive trace gases and have a major by linking the model to a detailed GIS database holding all relevant influence on boundary layer chemical composition. This conclusion information for initializing and driving the model such as data on was first reached for NOx (NO þ NO2), which was measured in vegetation (e.g. forest type) and soil properties (e.g. texture, soil pH, the boundary layer at Summit, Greenland at surprisingly high organic C content) and climate (either present day conditions or concentrations, and with a ratio to NOy that suggested a local projected future climate predictions). This approach demonstrated source. Measurements of NOx within the snow-pack interstitial air for the first time the huge regional differences in NO emissions revealed concentrations that were higher still, suggesting that the from forest soils across Europe as shown in Fig. 2.8, to estimate its snow-pack itself was the source, with a gradient to the atmosphere. significance on a regional scale and to unravel the importance of Subsequent measurements made in Antarctica confirmed that atmospheric N deposition for the magnitude of forest soil NO NOx production within the snow-pack was a feature of both emissions. polar regions (Jones et al., 2000). Additional measurements confirmed that NOx generated within the snow-pack was released 3. Biosphere atmosphere exchange of ammonia to the overlying boundary layer (Jones et al., 2001), contributing to the higher than expected NOx concentrations that were 3.1. Introduction encountered. The air chemistry of polar regions is a rapidly developing field Substantial progress has been made during the last five years in and extends substantially beyond interest in oxidized nitrogen, in understanding ammonia biosphere–atmosphere exchange. Experi- which surface processes clearly provide the major source of reac- mental studies have included controlled laboratory analysis, while tive oxidized nitrogen in Antarctic regions. Discussion of other trace a series of micrometeorological studies have assessed net fluxes gases, including halogen and mercury compounds are beyond the occurring under field conditions. In particular, major advances have scope of this review, however a valuable review of polar halogen been made in modelling the different aspects of ammonia exchange. chemistry and links to oxidized nitrogen chemistry is provided by This has included not just analysis of the drivers of the vertical flux Simpson et al. (2007). densities, but also a consideration of non-stationarities, such as advection effects and chemical interactions. Traditionally, micro- 2.8. Up-scaling and regional and global trends meteorological experiments were designed to avoid these effects, focusing as far as possible on ‘ideal’ micrometeorological conditions, The complexity of processes involved in NO emissions from soils so as to better quantify the vertical exchange processes, and develop has resulted in a significant uncertainty in the regional and global parametrisations for ‘dry deposition schemes’ in regional models source strength of soils for NO. However, different methodologies (Fowler and Duyzer, 1989; Fowler et al., 1998; Sutton et al., 1994; have been developed, e.g. relatively simple statistical models as Simpson et al., 2006). However, for ammonia, it has become well as process-based model approaches, to cope with the problem increasingly clear that these non-stationarities represent important of regionalisation of soil NO fluxes. The most widely used approach effects that are widespread in the real environment and need to be to calculate regional NO emissions from soils is based on the work quantified (Sutton et al., 2007, 2008c). of Yienger and Levy (1995). These authors consider land use and The developments in the last decade have arisen from a wide range respective background emission strengths, nitrogen fertilization of national and international projects. National studies have particu- rate (2.5% loss of applied nitrogen), temperature effects (three larly addressed exchange with key ecosystems of regional importance, classes: cold-linear, exponential and optima) as well as the pulsing such as ammonia losses from agricultural systems (e.g. Milford et al., of NO emissions following prolonged dry periods (four classes, 2001a; Walker et al., 2006; Wichink Kruit et al., 2007)andthe 5206 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

were complemented by the LIFE project, which added long-term ammonia flux data for a number of grassland, moorland and forest ecosystems (e.g. Flechard and Fowler, 1998; Erisman et al., 2001; Spindler et al., 2001). As understanding of ammonia exchange has improved and scientific ambition developed, increased attention has been given to integrating the different drivers of ammonia exchange processes. This has, for example, been reflected in the Braunschweig Integrated Experiment of GRAMINAE (e.g. Sutton et al., 2002, 2008a, 2009a,b), which linked a wide range of biospheric, atmospheric and management interactions as these control ammonia exchange with managed grassland. This integration has developed substantially under the NitroEurope Integrated Project (Sutton et al., 2007), in which interactions between the different components of nitrogen fluxes, including ammonia and oxidized nitrogen and their effect on the net greenhouse gas balance have been investigated. In parallel, major advances have been made in spatial modelling of ammonia fluxes, from individual forest edges to global scales (Theobald et al., 2004; Dentener and Crutzen, 1994; Hertel et al., 2006; Bleeker et al., 2006).

3.2. Advances in measurement methods

Before considering the developments outlined above in more detail, it is important to highlight that the advances have been critically dependent on improvements in measurement technology (See Table 1). At the start of the 1990s, ammonia flux measurements were still being made using wet chemistry and manual batch sampling with time integration of typically 2 h (e.g. Sutton et al., 1993a; Duyzer, 1994). The most important advance was the introduction of continuous wet chemistry methods for measuring ammonia profiles, including the AMANDA wet rotating denuder (Wyers et al., 1993) and the mini-Wet Effluent Diffusion Denuder (e.g. Blatter et al., 1993; Neftel et al., 1999). Although these tech- Fig. 2.8. Importance of atmospheric N deposition for NO emissions from forests soils. The niques are liable to malfunction, with effort and careful operation map shows the difference in NO emissions between a scenario with zero atmospheric they have produced many key datasets over the last 15 years N deposition and present day atmospheric N deposition. In large parts of central Europe but also Scandinavia forest NO emissions are likely to decrease significantly if atmo- (e.g. Erisman and Wyers, 1993; Sutton et al., 1995, 1997; Fowler spheric N deposition can be reduced to background levels. et al., 1998; Flechard and Fowler, 1998; Neftel et al., 1998; Milford et al., 2001a,b) and still represent the state-of-the-art as regards precise measurement of small ammonia fluxes (Wichink Kruit et al., ammonia inputs into semi-natural ecosystems of conservation value 2007; Neirynck and Ceulemans, 2008; Sutton et al., 2008b). (e.g. Wyers and Erisman, 1998; Neirynck and Ceulemans, 2008). A unique inter-comparison of four continuous wet chemical Collaborative international projects have sought to integrate and systems was made at the GRAMINAE Braunschweig Experiment extend these interests, making the comparison between ecosystem (Sutton et al., 2007, 2009b; Milford et al., 2009), which highlights types and looking at the interactions (e.g. Sutton et al., 2009a). the potential and limitations of the approach. Fig. 3.1 shows the The first European collaborative project dedicated to ammonia ammonia flux measured before and after cutting an agricultural exchange was ‘EXAMINE’. Attention was given to quantifying grassland, and following subsequent fertilization with calcium ammonia exchange with a range of European ecosystems, under both ammonium nitrate. The measurement systems were able to detect experimental and field conditions (e.g. Sutton et al., 1995; Schjoerring the wide range of ammonia fluxes, but the degree of agreement et al., 1998; Neftel et al., 1998; Meixner et al., 1996; Nemitz et al., varied greatly between days. This was a result of varying perfor- 2009b), including analysis of the surface gas-particle interactions mance of the different analysers, highlighting the need for highly between ammonia, nitric acid and hydrochloric acid (Nemitz and intensive instrument maintenance. Sutton, 2004). As part of EXAMINE a major collaborative analysis was Despite the improvements that have been made in the automation made in the North Berwick experiment, which provided a uniquely and reliability of the continuous wet chemical gradient methods (e.g. detailed examination of the processes controlling ammonia exchange Wichink Kruit et al., 2007; Flechard et al., 2007; Sutton et al., 2007), with an oilseed rape canopy (Husted et al., 2000; Nemitz et al., their remain several limitations, which have encouraged researchers 2000a,c; Sutton et al., 2000a,b). to seek alternative ammonia flux measurement approaches. In prin- In the second major European collaboration dedicated to ciple, many refinements have allowed the automated wet chemical ammonia, the GRAMINAE project analyzed the processes controlling methods to become more reliable and comprehensive (such as being ammonia exchange with grassland ecosystems across Europe (Sut- able to measure aerosol and acid gas gradients simultaneously, Trebs ton et al., 2001). This included assessment of both the bi-directional et al., 2006). However, the use of many moving parts can be consid- fluxes of ammonia with agricultural grassland – as these affect ered as inherently liable to faults. Similarly, the response times of atmospheric ammonia balance (e.g. Milford et al., 2001a; Mosquera these instruments are typically >5 min, which means that they et al., 2001), and with semi-natural grasslands as these are impacted are normally limited to the measurement of mean concentration by the atmosphere (e.g. Horva´th et al., 2005). These studies differences and vertical gradients. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5207

Table 1 Practical suitability of systems to measure ammonia biosphere–atmosphere exchange.

Chemical approach Advantage Disadvantage Application References

Box AGM REA EC Simple, cheap, high Batch ﬁlter packs Uncertain gas – aerosol split, batch JJ LLSutton et al. (1993a,b) air volume

Simple, cheap good Batch denuders Low air volume, batch JJ LLDuyzer (1994) gas-aerosol split

Automated batch Automated in ﬁeld, medium High laboratory processing cost, JJ LLLoubet et al. (2006, 2009) annular denuders cost, precise, high air volume only hourly, need two systems for ﬂuxes

Continuous annular Automatic sensitive, Cost, complexity, fault liable, JJ JJ L L Wyers et al. (1993), Erisman and Wyers (1993), denuders precise, high air volume gradient only Sutton et al. (1995, 2000b, 2001a) and Nemitz et al. (2001b)

Continuous parallel Automatic, sensitive, Cost, complexity, fault liable J J JJ L Nemitz et al. (2001a) and Hensen et al. (2008) plate denuders high air volume REA

Continuous Automatic, Cost, complexity, fault liable JJJJLHensen et al. (2008) mini-WEDD sensitive, precise

Continuous Automatic, sensitive, Cost medium complexity JJJJLFlechard et al. (2007) and Hensen et al. (2008) membrane precise, reliable denuder AIRmonia

Photo-accoustic Automatic, sensitive, Cost, complexity, not reliable JJ J L L Whitehead et al. (2008) in principle reliable

Tunable diode laser Automatic, sensitive, Very high cost, complexity, JJ LJShaw et al. (1998), Famulari et al. (2004), fast response (>10 Hz) maintenance Twigg et al. (2005) and Whitehead et al. (2008)

AGM: Aerodynamic Gradient Method; REA: Relexed Eddy Accumulation, EC: Eddy Covariance.

The beneﬁts of quantifying ammonia ﬂuxes using the gradient technique have been clearly demonstrated by the many papers published using this approach. In terms of informing our under- 50 ) standing of ammonia exchange processes and model development,

-1 Pre-cut s CEH this has almost exclusively been provided by measurements -2 25 FRI using the aerodynamic gradient method (90%), with a few studies 0 (in continental climates) applying the modified Bowen Ratio method (5%). By contrast, the key disadvantage of this method is -25 flux (ng m that it depends on micrometeorological stationarity, with no 3 change in the vertical flux with height. These flux/gradient methods NH -50 are not suitable for the study of exchange fluxes where advection of -75 ammonia from local sources is of interest (e.g. Loubet et al., 2001, )

-1 22/05/00 23/05/00 24/05/00 25/05/00 2006) and where gas-particle ammonia–ammonium interactions s Post-cut -2 CEH are signiﬁcant (e.g. Brost et al., 1988; Nemitz et al., 1996, 2004b). FRI To address some aspects of advection and air chemistry interac- 500 FAL-D FAL-CH tions, determination of ﬂuxes at a single height offers a way forward. If this can be achieved, in principle, deployment of replicate flux (ng m (ng flux 3 measurement systems at several heights could then be able to

NH 0 determine vertical ﬂux divergences (Sutton et al., 2007). Both the Eddy Covariance (EC) method and Relaxed Eddy Accumulation (REA) allow ﬂuxes to be determined from measurements at one height, and

) 31/05/00 01/06/00 02/06/00 03/06/00 -1 have therefore been the subject of several recent studies. The s 6000 Post-fert -2 CEH advantage of REA is that slow response ammonia measurements can FRI be combined with fast response switching, as has recently been 4000 FAL-D FAL-CH demonstrated in an inter-comparison of 4 REA systems for ammonia (Hensen et al., 2008). A further advantage is that programmed flux (ng m 3 2000 periods of random switching between air up- and down-drafts

NH allows automatic zero checks and the correction of any bias (Nemitz 0 et al., 2001a; Hensen et al., 2008). By contrast, the challenge for REA 06/06/00 07/06/00 08/06/00 09/06/00 and ammonia is that the concentration differential to be measured is typically much smaller than for the gradient method, which to a large Fig. 3.1. Inter-comparison of continuous profile systems for measuring ammonia fluxes extent cancels the benefit of auto-referencing. by the aerodynamic gradient method (AGM), from the GRAMINAE Braunschweig Experiment. Although highly scattered, this flux inter-comparison is unique and repre- Several recent studies have demonstrated the potential of fast sents the current state-of-the-art in chemical detection systems for ammonia fluxes. Increased emissions due to cutting of the underlying grass sward (29 May) and the effect response tunable diode laser absorption spectroscopy (TDLAS) of N fertilization with (100 kg N ha1, 5 June) are clearly shown (Sutton et al., 2007). for measurement of ammonia fluxes by eddy covariance 5208 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

1200 average concentration in the ecosystem canopy, both of which

TDLAS vary in time and in space (e.g. Sutton et al., 1995; Asman et al., 1000 QC-TDLAS 1998). Within the canopy, several sources and sinks combine together to determine the average ammonia concentration in the )

-1 800 canopy, including exchange with plant tissues through stomata, s

-2 with leaf cuticles and with decomposing leaf litter and the soil 600 surface (e.g. Denmead et al., 1976; Sutton et al., 1993b, 1998). (ng m

3 Ammonia within or immediately above the canopy airspace may 400 undergo chemical reactions, for example forming particulate matter, while depletion of gases within a plant canopy coupled Flux NH Flux 200 with altered microclimate can lead to evaporation of ammonium containing aerosol (Brost et al., 1988; Nemitz et al., 2004b). 0 Finally, the complex nature of ammonia sources and sinks in rural

-200 landscapes means that strong horizontal gradients of ammonia 29/04/2005 29/04/2005 30/04/2005 30/04/2005 30/04/2005 30/04/2005 occur. The result is that ammonia is not simply deposited from 14:24 20:24 02:24 08:24 14:24 20:24 above, but fluxes are often significantly influenced by advection Date, Time (GMT) effects, for example where advection from a ground level source beneath a micrometeorological reference height adds substan- Fig. 3.2. Fluxes of NH3 measured by eddy covariance over intensively managed grassland (Easter Bush, Scotland) several days after the application of liquid manure to tially to a net deposition flux (Loubet et al., 2001, 2008, 2009; the grassland (Sutton et al., 2007). Milford et al., 2001b). It is relevant to summarize the main influences on the primary drivers of exchange, the atmospheric ammonia concentration and the mean concentration of ammonia within the canopy. The first (Shaw et al., 1998; Famulari et al., 2004; Whitehead et al., 2008). of these is influenced partly by dispersion from adjacent In principle, reliable flux measurements can now be made for ammonia sources and partly by exchange with the surface itself. periods of large ammonia fluxes (e.g. after manured application), Over a surface which acts as an ammonia sink, above-canopy as has recently been demonstrated in an inter-comparison of ammonia concentrations are depleted relative to background two laser systems (Fig. 3.2). However, there was little correlation concentrations, while above canopy concentrations may be for fluxes <50 ng m2 s1, while the AMANDA systems have been 2 1 significantly enhanced if the surface is a net source (e.g. Sutton shown to be able to measure <10 ng m s (e.g. Sutton et al., et al., 2000a). 1998). Table 1 provides an overview of these and other systems The mean ammonia concentration of the canopy itself results for measuring ammonia fluxes. In principle, TDL and EC has the from the resolution of competing emission and deposition potential to be rated as high as the continuous gradient methods, processes with leaf cuticles, through stomata and with the ground but this still needs to be demonstrated by a more substantial body surface. The concept of ‘compensation point’ concentrations has of published measurements, particularly over longer time often been used to describe these relationships. The earliest view of periods and of a suitable quality for testing of models. a compensation point for ammonia related it to exchange through plant stomata with the leaf apoplast (Lemon and Van Houtte, 1980; 3.3. Key controls on biosphere atmosphere exchange of ammonia Farquhar et al., 1980). Under this interpretation, net ammonia fluxes would depend on the difference between what has since Fig. 3.3 summarizes the main processes affecting the net been termed the ‘stomatal compensation point’ (cs) and the exchange of ammonia with the atmosphere (Sutton et al., 2007). atmospheric concentration (ca). By contrast, subsequent studies The primary driver of ammonia exchange is the difference highlighted the fact that ammonia deposition rates were often between the atmospheric ammonia concentration and the faster than feasible by stomatal uptake, demonstrating the importance of ammonia deposition to leaf cuticles (e.g. Sutton et al., 1993a,b; Duyzer, 1994). The resolution between these positions was provided in the development of the concept of the ‘canopy compensation point’ (cc), which accounts for both bi-directional stomatal exchange and deposition to leaf cuticles (Sutton and Fowler, 1993; Sutton et al., 1995). Such canopy compensation point concepts have since been further developed to include bi-directional exchange with leaf surfaces and exchange with the ground surface under the canopy (e.g. Sutton et al., 1998; Flechard et al., 1999; Nemitz et al., 2001b). These inter-relationships are developed quantitatively in a two- layer canopy compensation point model (Nemitz et al., 2001b). One of the key points to note about ammonia compensation points is that they depend on the net solubility of ammonia in aqueous solution, which is largely dependent on its equililbrium with ammonium ions. By combining the temperature dependence of the Henry equilibrium and the ammonium dissociation equilibrium, Fig. 3.3. Summary of the key issues affecting the net land–atmosphere exchange of the gaseous ammonia concentration can be compared with a given ammonia. Each of these interactions can lead to ammonia fluxes changing with height þ þ ratio of [NH4 ]/[H ], which has been termed G (Nemitz et al., 2000c, above the ground. Ideally, flux measurements, based on e.g. relaxed eddy accumulation 2001a; Sutton et al., 2000b). On this basis, G can be used to provide or eddy covariance, made at several heights above the canopy would be used to quantify these effects, though until now such assessments have had to focus on the use temperature-normalized compensation points, for example þ þ of vertical profiles in mean ammonia concentration. cs ¼ f(T, Gs) where Gs ¼ [NH4 ]apoplast/[H ]apoplast. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5209

3.4. Effects of ecosystem type on ammonia It is feasible that these emission periods represent events biosphere–atmosphere exchange of desorption of previously deposited ammonia occurring in dry conditions. Conversely, it is also feasible that they represent It has long been established that ecosystem type affects net apparent ‘emissions’, being an artefact whereby horizontal ammonia fluxes (cf., Denmead et al., 1976; Horva´th, 1983; Sutton ammonia concentration gradients away from an adjacent ground- et al., 1993b, 1995; Duyzer, 1994). Overall, unfertilized ecosystems, based ammonia source (e.g. manure spreading, farms etc) lead to such as forest and moorlands are generally sinks for atmospheric an advection error. This would reduce the measured deposition ammonia, while fertilized and grazed agricultural ecosystems tend rate and could explain apparent ammonia upward fluxes in this to show bi-directional fluxes with some periods of deposition and context. This illustration emphasizes the complexity of measuring some periods of emission. Of course, the distinction is not absolute, ammonia exchange processes and highlights the need for further as smaller ammonia emissions may also occur from semi-natural investigation of each option. ecosystems (e.g. Sutton et al., 1995; Flechard and Fowler, 1998). The above example of mainly ammonia deposition to a forest However, such a general difference is clear, and can be explained by ecosystem may be contrasted with recently published measure- the increase in cs and cground that occurs in fertilized and grazed ments of ammonia fluxes over an intensively managed grassland in ecosystems. Two recently published examples of ammonia exchange the Netherlands (Wichink Kruit et al., 2007). The diurnal patterns in provide a useful basis to highlight these differences. ammonia concentration and net exchange flux are illustrated Neirynck et al. (2005) report ammonia flux measurements made in Fig. 3.5. Hourly ammonia concentrations in the air at this site using the AMANDA technique (Wyers et al., 1993) over a coniferous were again very large, 1–50 mgm3, with an overall mean of around forest in Belgium. Their forest site occurs in an area of intensive 10 mgm3. In this case, net emission occurred for around 40% of the livestock rearing, so that ammonia concentrations from some wind diurnal period (10:00–20:00), with net deposition at other times. directions are very large (5–25 mgm3) while for other wind sectors Wichink Kruit et al. (2007) also estimated the canopy 3 0 ammonia concentrations were more moderate (2–4 mgm ). Even compensation point (cc) based on profile estimation of c (zo ). They considering the effects of canopy wetness, in all conditions the then combined this with estimates of surface temperature to esti- 0 mean diurnal profiles show consistent net deposition to the forest mate G(zo )or‘Gc’ from the measurements (Fig. 3.6). Estimated 3 canopy. Curiously, the largest deposition fluxes occurred in dry values of cc were in the range 1–30 mgm , which is comparable conditions, which is unusual, as Rw would be expected to be smaller with other studies for managed grassland (e.g. Milford et al., 2001a; when the canopy is wet (Sutton et al., 1995; 1998; Nemitz et al., Sutton et al., 2001; Loubet et al., 2006), and substantially smaller 2001b). Although this difference is partly explained by different than the upper values implied for the forest in Fig. 3.4. Normalized values of Fmax during conditions of different canopy wetness, this for canopy temperature, the values of Gc were in the range does not to fully explain the difference. Further analysis by Neir- 200–11,000 through a period of May to October 2004, with a mean ynck et al. (2005) showed differences in the overall canopy resis- value of just over 2000. tance (Rc) for ammonia deposition with different canopy wetness and temperature, and with larger values of Rc occurring at higher 3.5. Modelling surface–atmosphere exchange of ammonia ammonia concentrations. Neirynck et al. (2005) did report periods of net ammonia Over recent years, the canopy compensation point approach has emission from their forest canopy (Fig. 3.4). These were recorded become the standard technique to model bi-directional ammonia during periods with winds from the high ammonia wind sector and surface–atmosphere exchange. Starting with the 1-layer models found to only happen at very large ammonia concentrations, which offsetting bi-directional stomatal exchange against deposition to occurred when air temperatures were larger than 15 C and relative leaf surfaces (Sutton and Fowler, 1993; Sutton et al., 1995, 2007), humidity less than 60%. Fig. 3.4 presents an intriguing result, since subsequent models have developed in several directions. The main according to the concepts of ammonia compensation points subsequent developments can be summarized as follows: a different picture should emerge, namely that periods of ammonia Treatment of multiple canopy layers: In addition to ammonia emission occur when atmospheric ammonia concentrations are exchange with the top part of the canopy, leaf litter and the soil small. By contrast, such a relationship is possible when emissions surface have been shown to be important sources of ammonia from a canopy are strong (and not compensation point driven), so emission into the plant canopy (e.g. Nemitz et al., 2000a). For an that it is the emissions from the surface that generate increased oilseed rape canopy Nemitz et al. (2000b) also highlighted the ammonia air concentrations. This phenomenon was also observed importance of an upper and lower part of the main foliage, dis- following harvest of an oilseed rape field (Sutton et al., 2000a,b). tinguishing the main foliage from an over canopy of oilseed ‘siliques’. In practice this three layer model becomes complex to parametrize, and there has now developed consensus that a two-layer model represents an appropriate balance of realistic description while avoiding excess complexity. A recent implementation of the 2-layer model is that of Personne et al. (2009) for the GRAMINAE Integrated Experiment (Sutton et al., 2009b). They used measured bioassay estimates of Gs and Glitter (Mattsson et al., 2008a,b; Herrmann et al., 2008) combined with an energy balance approach to calculate component resistances, showing close agreement with measured ammonia fluxes (Fig. 3.7). Treatment of cuticular fluxes: The initial parametrisations of the cuticular resistance (Rw) allowed only for deposition, dependent on relative humidity (Sutton and Fowler, 1993; Sutton et al., 1995) or vapour pressure deficit (Nemitz et al., 2000c, 2001b). As noted above for the forest example, ammonia deposited to a canopy Fig. 3.4. Dependence of ammonia flux on concentration in the high ammonia wind surface may also be re-emitted to the atmosphere, particularly sector during warm daytime conditions with dry canopy (Neirynck et al., 2005). under drying conditions. A first approach to simulate this effect 5210 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

Fig. 3.5. NH3-concentration (upper panel) and NH3-flux (lower panel) measurements above managed grassland in The Netherlands from 18 July until 15 August 2004 (summer 3 2 1 period). The horizontal axis represents time of the day (UTC). Local time is UTCþ2. The vertical axis represents the NH3-concentration (mgm )orNH3-flux (ng m s ). Diamonds A are calculated values for the half-hourly NH3-concentration or NH3-flux; the solid line (dd ) (with vertical 25 and 75 percentile bars) is the median of all half-hourly fluxes for that time. The dashed line (- - -) in the lower panel is the mean leaf wetness signal during this period (Wichink Kruit et al., 2007).

treated the leaf surface as a humidity dependent capacitance 3.6. Dynamic simulation of ecosystem C–N cycling (Qd), which would be in equilibrium with a non-zero leaf surface and ammonia fluxes concentration (cd)(Sutton et al., 1998). In this case an adsorption/ desorption resistance (Rd) is also defined. This first dynamic A disadvantage of the compensation point scheme for simu- approach had the advantage of being able to simulate ammonia lating ammonia fluxes outlined above is that empirical values of charging and discharging of the cuticle, but had the disadvantage G must be provided. The only way forward from this position is to that the leaf surface pH needed to be specified as an input. The develop models of carbon–nitrogen cycling that can simulate approach was further developed by Flechard et al. (1999) who G values for the different pools based on an understanding of the considered the full aqueous chemistry on leaf surfaces, dependent pool dynamics (cf. Massad et al., 2008). To date, the only such on multiple air pollutant inputs and potential leaching of base model to attempt this coupling is the PaSim model of Riedo et al. cations from leaf surfaces. In this model, leaf surface pH is solved by (2002). The model distinguished plant nitrogen pools into struc- ion balance, and the model is able to take account of the effects of tural nitrogen, substrate nitrogen and apoplastic nitrogen (a sub- other trace components such as SO2 on ammonia fluxes. Burkhardt pool of substrate nitrogen), linking these with plant uptake and et al. (2008) have recently extended this model to incorporate the growth processes. The model was parametrised based on measured two-layer approach with bi-directional exchange for each of the fluxes for a Scottish grassland (Milford et al., 2001b) and has leaf surface, stomata and ground surface. The cuticular resistance recently been tested for the Braunschweig Experiment (Sutton clearly responds to the chemistry of the liquid film on vegetation et al., 2009b). Overall, the model was able to simulate the larger and the combination of reactive gases present (Flechard et al., net emissions that occurred after cutting and after fertilization, as 1999). Even in the absence of additional reactive trace gases, the well as the decline in the 10 day period following fertilization. By cuticular resistance declines with increasing NH3 concentration. contrast, the component fluxes were less well described. Bioassays, In a series of chamber experiments Jones et al. (2007) quantified chamber measurements and within-canopy profiles during the the relationships between ambient NH3 concentration and the bulk Braunschweig Experiment (Mattsson et al., 2008a,b; Herrmann canopy resistance for a range of moorland vegetation as shown in et al., 2008; Nemitz et al., 2009b) highlighted leaf litter as being Fig. 3.8 in which the non-stomatal ‘cuticular’ resistance is seen to a key source of emission following cutting. This source is currently increase lineary with NH3 concentration, leading to much smaller not simulated in PaSim, which simulated that increased emissions deposition at high concentrations than if deposition velocity after cutting were due to an increase in apoplastic ammonium. The remained constant with concentration as is usually assumed. bioassays indicated that the foliage was more likely to be a sink of D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5211

0 þ þ 0 Fig. 3.6. Derived canopy compensation points (cc ¼ c(zo )) (upper panel) and ratios between NH4 and H concentration (Gc ¼ G(zo )) (lower panel) from the end of May until the end of October 2004 (diamonds) and the constant value (2200) that is normally assumed for modeling (line) (Wichink Kruit et al., 2007).

soil/litter ammonia emissions, highlighting the need for improved 1. That unreplicated ammonia flux measurements in most studies ecosystem modelling of ammonia exchange that accounts for litter are highly uncertain and need to be considered with caution decomposition processes (Sutton et al., 2000b). when compared with model estimates. 2. That advection effects can significantly influence measured 3.7. Integrating ammonia exchange processes ammonia fluxes, both due to dispersion away from nearby point sources (correction for advection effects increases net The preceding sections have highlighted the many processes deposition) and due to emissions from an emitting field itself and interactions that combine to regulate ammonia fluxes between (correction for advection increases net emission). vegetation and the atmosphere. It thus becomes a major challenge 3. That gas-particle interactions had a minor effect on measured to integrate each of these processes to develop a holistic view. It is ammonia fluxes, though the relative effect on calculated aerosol necessary to quantify the interactions in each case in order that deposition rates was significant (being the cause of apparent valid conclusions can be obtained. This creates a major challenge aerosol emissions). for experimentalists to be able to address all the questions in the 4. That reasonable agreement can be made between relaxed eddy field. For example, in the absence of measurements of horizontal accumulation for ammonia and the aerodynamic gradient concentration profiles, it is difficult to quantify the potential for method, though measurements are not yet sufficiently precise advection effects to have influenced the results presented in to detect flux divergence (except for possible cases of extreme Fig. 3.4. Similarly, it remains an open question in most studies advection errors). whether gas-particle interactions have a significant influence on 5. That net emissions from this grassland canopy are controlled by measured ammonia fluxes. the recapture of leaf litter ammonia emissions by overlying It was with such interactions in mind that the GRAMINAE foliage and the interaction of cuticular exchange pools with Integrated Experiment was designed. A number of findings from mainly stomatal uptake of ammonia from the leaf litter emis- this experiment have already been mentioned, but the experiment sions. Net emissions increase following cutting due to exposure demonstrates both the challenges and the power of developing an of the litter and cutting induced senescence, with a similar integrated approach. Fig. 3.9 summarizes each of the issues and recapture process affecting net emission following fertilization. measurement methods that were investigated during this experiment (Sutton et al., 2008a). The key conclusions from this study A range of models is able to simulate the dynamics of net have been summarized by Sutton et al. (2009b) and include: ammonia exchange with the managed grassland, but further 5212 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

4500 key challenges include the climate dependence of net ammonia Measured flux 4000 emission and deposition, and the characteristic ﬂuxes of other Modelled flux (Gamma Litter) ecosystems in the world.

) 3500 -1

s In principle the models of ammonia exchange incorporate the 3000 -2 main features of environmental conditions and could therefore be 2500 applied in different climates. Here the limitations include the lack of 2000 available data for empirical factors such as G values and the back- 1500 ground data to extrapolate to conditions with different climates. fluxes (ng m fluxes (ng 3 1000 Currently, the estimates of G have mainly been derived for cool NH 500 European conditions and for a very limited number of ecosystems. 0 Although there have been many studies of ammonia emission from -500 fertilized tropical systems, such as rice and maize, there are few 22-May 29-May 05-Jun 12-Jun published studies of ammonia fluxes over semi-natural unfertilized tropical ecosystems. The rates of ammonia deposition or emission Fig. 3.7. Comparison of ammonia fluxes simulated by a two-layer canopy compensa- in these situations are thus highly uncertain. Given the differences tion point model (SURFATM-NH3) with measured fluxes (Fmg) during the GRAMINAE Braunschweig Experiment. For this model scenario, the ground emission is assumed to in biology of these systems, measurements are required to underpin originate from leaf litter based on measured Glitter (Personne et al., 2009). modelling approaches. A modest degree of climate change (e.g. þ2 C) is a much easier matter to simulate, for example based on the analysis of temperature attention is needed to develop dynamic treatments of ammonia effects within existing datasets. The thermodynamics of ammonia emissions from leaf litter decomposition. solubility and dissociation are rather straightforward, indicating for example a doubling in cs every 5 C increase for a given value of 3.8. Future challenges for ammonia exchange G (Sutton et al., 2001). However, caution is needed before making climate change simulations on this basis. Analysis of the PaSim model The results from the GRAMINAE Integrated Experiment provide under different temperature regimes showed that net ammonia a microcosm of some of the key challenges to measure ammonia fluxes for Easter Bush in Scotland (cf. to measured fluxes of Milford fluxes and model the process interactions. In a wider perspective et al., 2001b) were quite insensitive to temperature. For example, increased temperature (in the absence of moisture limitation) led to increased grass growth which diluted available nitrogen pools, thereby reducing G values (Sutton and Milford, unpublished simulations). Similarly, increases in wetness, while favouring smaller values of Rw may also lead to increased rates of leaf litter decomposition, favouring ammonia emissions. To take another example, in colder conditions, NH3 from manure application to the land surface tends to be emitted at smaller rates, but the emission lasts longer, especially if a waterlogged or frozen soil conditions prevent infiltra- tion. With these illustrations in mind, it becomes a major future challenge to generalize how ammonia fluxes might change in the future under different climatic regimes.

4. Sulphur dioxide

4.1. Introduction

There are three very different spatial scales relevant to the exchange of SO2 at terrestrial surfaces, first the micro-scale, at which the chemical and biological interactions occur (Fig. 1.1). Second is the spatial scale at which most of measurement and interpretation takes place, which is the field scale (averaged over 103–105 m2)for measurements using micrometeorological methods. Lastly, the application of knowledge of the surface exchange process is primarily at regional to continental scales to characterise the fluxes and budgets within chemistry transport models (CTM) and comparisons with the concentration fields observable from satellites. The measurements have mainly been made at the field scale using micrometeorological methods, although there have been some laboratory studies, mainly in the early days of SO2 dry deposition research. The initial measurements were used to estimate the regional scales of dry deposition, often using a fixed deposition velocity as a key variable within long-range transport Fig. 3.8. The relationship between ambient ammonia concentrations and the cuticular models (e.g. Fisher et al., 1978). With larger datasets of measure- resistance to deposition for moorland vegetation. A significant difference was found ments covering a wide range of conditions, it is clear that rates between day and night for the bulk canopy resistance (R ), which included both c of dry deposition vary considerably in time and space (Fowler stomatal uptake and deposition to the leaf surfaces. Once the effect of the stomatal resistance (Rs) was accounted for, the cuticular resistance (Rw) was found to approx- and Unsworth, 1979) in particular because the sinks available at imately constant day and night (Jones et al., 2007). terrestrial surfaces, including the stomata in vegetation, leaf D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5213

Estimation of Advection of Quantification of Interactions with acid

farm-scale NH3 NH3 from nearby energy balance & gases and ammonium emissions sources & effects environ controls on particles & effects

from plume on vertical fluxes NH3 exchange on net NH3 fluxes measurements

Continuous

measurement of NH3 fluxes by gradient Effects of dew and REA approaches Effects of cutting & leaf surface & N fertilization chemistry events & choices on NH fluxes 3 NH3 compensation points of foliage Plant bioassay Within-canopy determination of cycling of NH3 fluxes NH3 emission potential

Determination of Effects of leaf senescence

within-canopy NH3 release from and plant species on turbulent exchange litter decomposition NH3 emission potential

Soil chemistry interactions

with plant N uptake & NH3 fluxes

Fig. 3.9. Overview of issues addressed by the GRAMINAE Integrated Experiment (Sutton et al., 2008a).

surfaces and the presence of liquid water on vegetation from dew 4.2. Worldwide advances in SO2 flux monitoring and modelling or rain, present a variable absorbing surface. The data have shown the role of atmospheric composition and surface leaf water chem- 4.2.1. Asia istry in controlling canopy resistance. Sulphur dioxide dry deposition to vegetated surfaces is largely Most dry deposition measurements of sulphur dioxide over the controlled by non-stomatal processes, but in many arid ecosystems last 30 years have been made in N. America and Europe, and have and deserts of the world where vegetation is sparse, the nature and served as a basis for the parameterisation of dry deposition models pH of soils determine the sink strength. In Asia, substantial efforts (Erisman,1994; Smith et al., 2000; Zhang et al., 2002), which in turn have for example gone into the characterization of SO2 uptake by have been applied to ecosystems in different parts of the globe. loess soils, given their large geographical representation in However, most SO2 emission and deposition now occurs outside Northern China, their alkaline nature and their ability to neutralize N. America and Europe. Asia’s contribution in 1985 of 20% to global atmospheric acidity and to serve as an oxidation medium for anthropogenic SO2 emissions has doubled since then, reaching 37% SO2. Both micrometeorological and laboratory- or field-based by the year 2000, of which 23% is emitted by China alone and 5% by flow reactor methods were deployed. New micrometeorological India. measurements over forests and short vegetation have also been Southern China is one of the world’s most sulphur polluted reported over the last 10 years in the region, reflecting the growing areas. Paradoxically, in Northern China, where ambient SO2 concern over increasing sulphur emissions and deposition to concentrations are very large, rainfall is generally alkaline, and the ecosystems. areas polluted by acid rain do not necessarily correspond to the areas of high SO2 emissions. One of the reasons for this discrepancy 4.2.1.1. Sulphur dioxide deposition to soils. Utiyama et al. (2005) is the presence of alkaline soils (yellow sand) distributed over measured dry deposition to loess soil and dead grass in Beijing the arid areas of N.W. China (e.g. the loess plateau and Gobi desert), using the aerodynamic gradient method, though in neutral condi- the windborne erosion of particles with high base cation concen- tions 22% of the time. In stable or unstable thermal stratification, trations can neutralize atmospheric acidity (Utiyama et al., 2005). they used a surface reaction concept for inferring dry deposition. Loess soil, which covers vast areas of the Eurasian continent Two surface kinetics models were considered: either i) the reaction extending from N.E. China to Central Asia, contains Ca in large occurs in soil pores and SO2 molecules diffuse through porosity quantities, and calcium carbonate (CaCO3) reacts with atmospheric while reacting with alkaline sites on the pore surface; or ii) the SO2, to form calcium sulphate (CaSO4). Thus, even bare soil without adsorption mechanism is of Langmuir–Hinshelwood type, where vegetation may be a significant sink (Sorimachi and Sakamoto, the partial pressure of SO2 and its desorption pressure from the site 2007), which may affect the regional SO2 budget if the process is are in equilibrium. The model parameters are then fitted so that the inadequately quantified in dry deposition models. resulting (modelled) vertical SO2 concentration gradient matches In this section we review research and monitoring from the last the observations. Measured deposition velocities (Vd) were in the 1 decade, including SO2 dry deposition measurements from Asia, range 1–12 mm s . North America and Europe, as well as findings from long-term flux Sorimachi and Sakamoto (2007) conducted laboratory-based monitoring experiments. The current state of knowledge concern- flow-reactor measurements of SO2 deposition to soil samples from 12 ing mechanisms of SO2 dry removal from the atmosphere is sites in the arid loess plateau and deserts of Northern China. Canopy reviewed, with consequences for temporal trends in atmospheric resistances in the range 28–650 s m1 (with a mean of around concentration and deposition, and key future research areas are 200 s m1) were found to be dependent on RH, as was S(IV) oxidation identified. to S(VI). It was hypothesized that Northern China soils, which are 5214 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 much more alkaline than in Southern China, are a greater sink for SO2 The latter can only provide crude estimates of deposition rates, as and a neutralizing buffer for acidifying atmospheric deposition surrogate surfaces do not adequately account for the complexity of (Sorimachi et al., 2004). By comparison, in modelling SO2 deposition natural surfaces, but they do allow continuous monitoring at to Asia, Xu and Carmichael (1998) used a fixed Rc for deserts of a number of sites and help to detect trends. The use of inferential 500 s m1, which is clearly too high in the case of Northern China methods requires underpinning measurements of surface resistance deserts. A flow-reactor was also used by Sakamoto et al. (2004) to to representative surfaces to parameterise the models used. It is also determine SO2 dry deposition to yellow sand and soil-mediated SO2 important to note that long-term changes in canopy resistance are oxidation by O3. The deposition velocity for SO2 increased with RH likely, especially in regions in which the relative ambient concen- due to the positive effect of RH on the SO2 oxidation rate. trations of SO2 and NH3 change with time, as for example in Europe during the period 1990–2005 (Fowler et al., 2001c, 2007). 4.2.1.2. Micrometeorological measurements over vegetated Ta et al. (2005) thus provided long-term sulphur dioxide dry areas. Matsuda et al. (2006) reported micrometeorological (aero- deposition estimates across Gansu Province, China, using K2CO3- dynamic gradient) flux measurements of SO2 and O3 over a tropical coated surrogate sulfation plates. Samples were taken monthly for (teak) forest in Northern Thailand in dry and wet seasons. The 11 years at 48 sites distributed across 11 cities in the province. deposition velocity for SO2 in the dry season was rather low, in the The data showed that cumulative SO2 dry deposition fluxes were 1 1 range 1–3.1 mm s in daytime and 0.8–1.1 mm s in night-time. closely related to local SO2 emissions, and had seasonal variations In the wet season, however, Vd was much higher due to enhanced with maxima in winter and minima during summer as a result of non-stomatal uptake in wet conditions, with values in the range higher winter and lower summer SO2 emissions and concentra- 1 1 9.5–13.9 mm s in daytime and 2.6–4.2 mm s in night-time. The tions. Monthly average SO2 deposition velocities, however, peaked data were compared with a recent non-stomatal resistance scheme in April–July at 11–27 mm s1, and minimum values were observed (Zhang et al., 2003a), and it was concluded that extended experi- in January at 2–10 mm s1. mental SO2 dry deposition studies are needed in the tropics, while Inferential models (Erisman, 1994; Smith et al., 2000; Zhang Zhang et al. (2003a) recommend more studies to quantify the et al., 2002) may be used to estimate dry deposition at observation different effects of dew and rain on SO2 deposition. sites, where single-height ambient concentration measurements Sulphur dioxide dry deposition was also measured by Matsuda are available together with standard meteorological data. Model et al. (2002) over a red pine forest located in Oshiba Highland, parameters, however, have been largely derived from European and Nagano, Japan, using a Bowen ratio technique. The median daytime N. American studies and may not necessarily be adequate for Asian (12:00 to 14:00) deposition velocity was 9 mm s1. Measurements vegetation and soils, and numerical evaluations need to be carried compared favourably with estimates by an inferential model for out. Thus Takahashi et al. (2002) simulated the dry deposition of wet conditions, but for dry or mixed wet-dry surfaces there were SO2 to a Japanese cedar (Cryptomeria japonica) forest located in large differences between model and measurements. The authors Gumma Prefecture, based on the results of 1-year’s concentration 1 ascribed the discrepancy to a relative humidity threshold value measurements. The mean modelled Vd at this site was 8.8 mm s used in the inferential scheme to characterise canopy wetness, and (Takahashi et al., 2001). The inferential estimate of the dry sulphur pointed to the need for a refined parameterisation of the cuticle or deposition flux was 11.1 mmol m2 yr1 (3.6 kg S ha1 yr1), which external leaf surface resistance. compared well with the net throughfall flux (12.4 mmol m2 yr1, 1 1 In a study of SO2 and O3 dry deposition to short grassy vegeta- or 4.0 kg S ha yr ). Over a broadleaf forest on typical red soil of tion over an alkaline soil (pH ¼ 9.2) near Beijing, using the Southern China, Xu et al. (2004) simulated Vd for SO2 and partic- 2 aerodynamic gradient method, Sorimachi et al. (2003) measured ulate SO4 , as well as their atmospheric deposition fluxes. The 1 1 mean Vd values of 2 (1) mm s and 4 (2) mm s in late summer simulations indicated that about 99% of the dry sulphur deposition and early winter, respectively. Although the grass was lush and flux in the forest resulted from SO2, which contributed over 69% of thick in the late summer, and senescent and leafless in the early the total (wet þ dry) annual sulphur deposition. winter observation period, there was no difference in the mean Rc By comparison, Wang et al. (2003) computed dry deposition 1 1 2 (180 270 s m and 180 300 s m , respectively), but the fluxes of SO2 and SO4 for 1 year to agricultural land over red soil uncertainties given reveal a large variability in measured Rc. The (pH ¼ 5.3–5.8) in the Jiangxi province of Central China. The crops difference in Vd stemmed from the higher aerodynamic (Ra) and grown were rice paddies and oilseed rape. Sulphur dioxide 1 1 quasi-laminar sub-layer (Rb) resistances in late summer than in concentrations were measured 8 times day , 7 days month , using early winter. The absence of vegetation and stomatal uptake in a bubbler method. Annual mean modelled estimates of Vd were 1 1 2 early winter, which might otherwise have reduced the SO2 sink 3.8 (0.16)mms for SO2 and 0.20 (0.12) mm s for SO4 . strength, seems to have been compensated for by the soil alkalinity. Measured monthly mean concentrations ranged from 9 to As the soil was more exposed and the in-canopy aerodynamic 163 mgSm3 (6.7–121 ppb), with an annual mean of 64 mgSm3 resistance was reduced, the soil surface offered more adsorption (47 ppb). Estimates of total monthly wet and dry deposition of SO2 2 1 and reaction sites for SO2, with the result that the field was an and SO4 ranged from 2.2 to 20.3 kg S ha with an annual total 1 equally efficient SO2 sink in early winter as in summer. deposition of over 100 kg S ha , of which 83% was via dry deposi- The deposition velocity for SO2 was measured by Jitto et al. tion, accounting for over 90% of total S input to farmland in this area. (2007) during a 1-year experiment over a canopy of irrigated rice paddy in Thailand using the Bowen ratio technique. The deposition 4.2.2. North America velocity was highest around noon and lowest at night. Seasonally- Few long-term datasets of SO2 dry deposition monitoring have 1 averaged values of Vd were 6.7, 12.5, and 15.1 mm s in the winter, emerged over the last 10 years, reflecting the declining importance of summer, and rainy seasons, respectively. SO2 as an acidifying input relative to NOy and NHx. Advances have nonetheless been made in inferential modelling of SO2 uptake, 4.2.1.3. Long-term deposition studies and inferential modelling. As especially regarding the quantification of the non-stomatal (external) alternatives to costly and labour-intensive micrometeorological leaf surface resistance, which serve as a basis for simulating regional measurements of dry deposition, several authors in Asia have esti- patterns of SO2 deposition (Zhang et al., 2002, 2003b). mated long-term SO2 deposition using monitored concentration data Micrometeorological SO2 flux data from 5 sites (2 forests, a corn and inferential models, or long-term artificial collection devices. field, a soybean field and a pasture) in eastern USA (Finkelstein et al., D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5215

2000; Meyers et al., 1998) were compared with modelled data by that the flux remained nearly constant. The measurements of the Zhang et al. (2003a), with the specific objective of evaluating the new atmospheric terms (Ra and Rb) revealed no trend, thus the trend in non-stomatal resistance scheme of the new Canadian model (Zhang Rc is not caused by changes in turbulence, and are clearly a conse- et al., 2002, 2003b). Over the forest sites, Finkelstein et al. (2000) had quence of the chemical affinity of the surface changing with time. noted that wetness tended to increase deposition velocity, but that These dry deposition measurements have proved valuable in the nature of wetness (rain or dew) and its chemistry also controlled explaining the consistently larger decline in ambient SO2 concen- canopy resistance. Non-stomatal surfaces like leaf surface, stem, tration than in emissions in Europe. In the absence of these flux trunk and ground were important sinks for SO2,andtheauthors measurements it would be a matter of speculation as to the under- concluded that a better understanding of surface chemistry and lying cause of the faster decline in ambient concentration than water film chemistry was needed. emission. Even with these measurements there remains the possi- Dew formation has long been recognised as an important sink for bility that SO2 oxidation rates have increased due to the growing SO2 (Fowler and Unsworth, 1974, 1979). In more recent work Meyers oxidizing capacity of the atmosphere and have contributed to the et al. (1998) show that dew is the reason for the relatively high early relative changes in emission and deposition (non-linearity). It will be morning deposition rates at 2 of the 3 low vegetation sites studied in necessary in the further analysis and interpretation of European Eastern USA. Recognizing the weakness of existing North American pollution climate data to carefully examine the relative importance parameterisations (e.g. Meyers et al., 1998) in predicting SO2 depo- of the different contributors to the observed trends in concentration sition rates to non-stomatal surfaces, especially in wet canopies, and deposition and quantify the relative importance of changes in Zhang et al. (2003a) demonstrate that the AURAMS scheme (Zhang dry deposition and oxidation rates in the long-term trends. et al., 2002) performed well at these 5 sites, using different resistance values for dew and rain. The revised non-stomatal resistance scheme 4.2.3.2. Other recent European datasets. The SO2 flux–gradient data (Zhang et al., 2003b) includes a treatment of in-canopy transport, soil obtained over short vegetation by Feliciano et al. (2001), collected and cuticle terms, and is a function of relative humidity, leaf area over a period of 3 years in the mid 1990s at 3 different sites in index and friction velocity. For wet canopies, the cuticular resistance Portugal, were important in providing Rc estimates for the Medi- is treated differently for dew and rain. terranean region of Southern Europe. The 3 sites had contrasting pollution climates, with a coastal, oceanic, humid meadow in 4.2.3. Europe N. Portugal, a hot and semi-arid pseudo-steppe and a site located in 4.2.3.1. Long-term flux monitoring in the UK. Sulphur dioxide fluxes a mostly dry, intensive agricultural area, both in S. Portugal. Median have been monitored continuously since the mid 90s at two rural canopy resistances varied from 140 s m1 to 200 s m1 and although sites in the UK, over agricultural land at Sutton Bonnington in the stomatal uptake was important when vegetation was biologically English Midlands, and over moorland at Auchencorth Moss in active, the annual deposition was dominated by non-stomatal S. Scotland (Fowler et al., 2001c, 2005, 2007). The dry deposition mechanisms on wet surfaces. The night-time canopy resistance, measurements have continued to bring surprises over the last 10 a proxy for the non-stomatal resistance, increased with decreasing years. At Sutton Bonnington, the ambient concentrations have relative humidity at all 3 sites. A comparison of nocturnal Rc for the declined from about 2.8 ppb in 1996 to current values close to southern sites showed that, for a given level of relative humidity, the 1.4 ppb and yet the deposition velocity continues to increase due to Rc at the intensive agricultural site was systematically lower than at continued reduction in the canopy resistance (Rc)(Fig. 4.1). Over the pseudo-steppe site, which is used more extensively for grazing the monitoring period the canopy resistance has almost halved and and hay production. Although the authors make no mention of NH3 is now about 70 s m1. The consequence of the steady decline in being measured at these sites, it might be hypothesized that a higher canopy resistance along with a decline in ambient concentration is NH3 concentration at the intensive agricultural site may have been

10 9 8 7 6

5 NHNH33 SO 4 SO22 3

Mixing ratio (ppb) 2 1 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 )

-1 0.6 140

0.5 120 R SO2/NH3SO2/NH3

100 c c2 SO 0.4 Rc (Wheat) 80 2

0.3 m (s 60

0.2 -1 molar ratio (ppb ppb

40 ) 3 0.1 20 /NH 2 0 0 SO 1995 1996 19971998 1999 2000 2001 2002 2003 2004

Fig. 4.1. Changes in the mean concentrations (ppbV) and ratio of ammonia and sulphur dioxide and in the May–July canopy resistance for SO2 deposition on Wheat at Sutton Bonnington between 1996 and 2003. 5216 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 responsible for the observed lower nocturnal Rc, compared with the extensively-managed, steppe-like grassland. The development of low-cost systems for the long-term monitoring of SO2,NH3 and other trace gas fluxes holds promise for widening the range of dry deposition datasets for comparison with inferential models. Hole et al. (2008) presentan18-monthdatasetof SO2 fluxes acquired with a conditional time-averaged gradient (COTAG) system (Fowler et al., 2001b; Famulari et al., in press)in a semi-alpine ecosystem in Southern Norway. The mean annual SO2 deposition velocity was 4.0 mm s1, although the dataset included some negative deposition velocities (upward fluxes), and the annual 1 mean Vd was 13.0 mm s if only the positive values were included. The authors report evidence of enhanced SO2 deposition rates during anepisodeinNovember2005whentheNH3/SO2 ratio was high, and conversely of decreased SO2 uptake and increased NH3 uptake in November 2004 when the NH3/SO2 ratio was low. Comparison with the inferential model by Zhang et al. (2002, 2003b) was satisfactory but the model could not reproduce the large observed variability in exchange rates, which may result from NH3–SO2 co-deposition processes not being included in their resistance scheme. More experimental evidence of the mutual influences of NH3 and SO2 concentrations on their deposition rates was obtained by Derome et al. (2004), though not by micrometeorological measurements but using bulk precipitation collectors and throughfall measurements in Scots pine canopies in SW Finland. The study was conducted over a 6-year period (1993–1998) in the vicinity of a Cu–Ni smelter, which emitted large amounts of gaseous NH3.These emissions were shown to have strongly enhanced the scavenging of atmospheric SO2 by the pine canopy, resulting in increased levels of N and S deposition and increased foliar N and S concentrations. In an NH3 fumigation experiment, Cape et al. (1998) had previously described similar findings over a Scots pine forest in Central Scotland, with the canopy resistance for SO2 decreasing with elevated NH3 concentration. Although NH3 concentrations were not measured in Fig. 4.2. A schematic representation of the dynamic canopy compensation pollution the Finnish study (Derome et al., 2004), they were likely higher than model for SO2 and NH3 exchange over vegetation (from Flechard et al., 1999). normally encountered in the countryside, except near animal housing in areas of intensive agriculture, where such processes could 3 be significant. increased to 2 mgm to provide sufficient NH3 to neutralize the acidity from the ambient SO2 oxidation in solution. The conse- 4.3. Control of surface uptake rates by leaf cuticular chemistry quence of the increase in ambient NH3 is to decrease the canopy resistance for SO2 and increase the deposition rate of SO2 to the A number of authors have addressed the issue of the chemical maximum under the prevailing atmospheric conditions. Demon- control of surface pollutant uptake rates (e.g. Flechard et al., 1999). strating a close link between SO2 deposition and ambient NH3 is not The most important finding for SO2 deposition is that the rates of new, as this was predicted in earlier work in the Netherlands (Van deposition are controlled mainly by the chemistry at the vegeta- Hove et al., 1989). However, this work quantified the process tion–atmosphere interface, and that as the surfaces are wet most of the time, the processes are regulated by chemical processes within the thin film of moisture. In principle, many compounds influence 10 the chemistry of this surface layer, including plant exudates and soil )

2 0 derived compounds, but the key reactant for SO2 is NH3. Thus the SO -10 ambient concentrations of SO and NH essentially regulate the pH -1

2 3 s of the surface moisture and thus control the uptake of SO2. The -2 -20 full surface chemistry of the process has been incorporated into -30 Meas. FSO2 a dynamic mechanistic model shown in Fig. 4.2 (Flechard et al., χ Mod. FSO2 ( NH3 = ambient) -40 χ -3 1999). The chemistry of the surface water film is initialised in the flux (ng m Mod. F ( = 2 μg m 2 SO2 NH3 ) model using measured precipitation chemistry, the model then FSO2, max SO -50 simulates the dynamic responses of the net land–atmosphere -60 exchange of SO2 as the ambient concentrations of the reactive trace gases and meteorological conditions change. The model has been shown to provide good agreement with observed 30 min average fluxes for several days. An example is provided in Fig. 4.3, for a five-

day period at Auchencorth Moss in the Scottish Borders. The 21/03/95 12:00 22/03/95 00:00 22/03/95 12:00 23/03/95 00:00 23/03/95 12:00 24/03/95 00:00 24/03/95 12:00 25/03/95 00:00 25/03/95 12:00 26/03/95 00:00 26/03/95 12:00 general agreement between measured and modelled fluxes is Fig. 4.3. A comparison between measured and modelled SO2 fluxes at Auchencorth excellent during the three-day period, 21st March to 23rd March Moss over the period 21-3-95 to 26-3-95 showing the influence of increasing ambient 1995. From the 24th March, the observed NH3 concentrations are NH3 concentration on SO2 flux (from Flechard et al., 1999). D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5217 correctly for the first time, demonstrated the effects in field period has meant that the SO2/NH3 ratio has decreased dramatically, conditions at ambient concentrations and provided a mechanistic resulting in a reduced Rc for SO2 (Fig. 4.1). The data for Fig. 4.1 are of model incorporating the full chemical scheme. course site specific and the footprint of the measurements in Not- tinghamshire is only 104–105 m2, but this trend may be regarded as 4.4. Advances in deposition modelling representative for the regions in which ambient SO2 concentrations have declined by up to an order of magnitude since 1970 and The magnitude of dry deposition at the national and regional includes much of central and eastern England and the industrial scales requires that process-based, rather than empirical, parame- regions of Germany, France, the Netherlands and Belgium. While terisations be implemented in atmospheric models, accounting for ambient SO2 was a relatively good proxy for total atmospheric and variations in surface chemical characteristics driven by local pollu- leaf surface acidity 15 or 25 years ago, the relative share of SO2 tion climates. The observation of changes in deposition velocity from compared to other inorganic atmospheric acids (e.g. HNO3 and HCl) the European SO2 deposition studies of the 90s is now widely known is now much smaller. The NitroEurope network of 56 DELTA and is being used by EMEP to explain growing discrepancies in the samplers across the European continent currently provides monthly model-measurement comparisons over Europe. The work has led to mean concentrations of HNO3 and HCl as well as SO2 and NH3 and þ 2- modifications of the EMEP model (Simpson et al., 2003) to simulate aerosol NH4 ,NO3 and SO4 (Tang et al., 2009), with a view to vali- the temporal trends, resulting in an increase in Vd for SO2 over dating European concentration fields of concentration and deposi- many parts of the continent, and driven by the long term, large scale tion for these species. The data show (Fig. 4.5) that the geometric decrease in the SO2/NH3 ratio (Fig. 4.4). The new scheme, for non- mean mixing ratios of SO2, HNO3 and HCl across the network are 0.4, stomatal resistance of both NH3 and SO2, incorporates an acidity to 0.35 and 0.15 ppb, respectively, so that, on average, SO2 makes up alkalinity (SO2/NH3) molar ratio as a scaling factor for resistances. For only about 40% of the sum of acids (SO2 þ HNO3 þ HCl). Further, the SO2, two non-stomatal resistances Rns,wet and Rns,dry are calculated as data indicate that at some sites (e.g. most Danish, French and Italian a function of the SO2/NH3 ratio, and a function of relative humidity is sites), the acidity is largely dominated by HNO3 and HCl, which are used for the transition from dry to wet when the surface cannot be considered in most models (e.g. Simpson et al., 2003) to be deposited w 1 considered fully wet or fully dry. at the maximum rates allowed by turbulence (Rc 0sm ). Under The EMEP non-stomatal deposition scheme has also been used such conditions, the proxy (SO2 þ HNO3 þ HCl)/NH3 would seem in field-scale inferential modelling of N and S dry deposition as part more appropriate to quantify the relative importance of surface of the NitroEurope project, using low-cost, long-term atmospheric acidity and alkalinity in model parameterisations, than the ratio of trace gas and aerosol DELTA samplers (Tang et al., 2009). Another SO2 alone to NH3. Clearly the surface affinity for SO2 uptake will implementation of the parameterisation was made by Zimmer- depend on the presence of fast-depositing, strong acids as the acidity mann et al. (2006) for the simulation of atmospheric deposition to is no longer SO2-dominated, and this needs to be accounted for in Norway spruce, using the SPRUCEDEP SVAT model, and comparison extended surface resistance parameterisations. with throughfall measurements and a canopy base cation budget model. The agreement between (inferential & canopy budget) 4.5. Future challenges modelling and observations was very good for S and oxidized N. Here, the contribution of dry to total (dry þ wet) deposition was The principal controls over SO2 deposition to terrestrial surfaces around 60% for S and for both reduced and oxidized N. have been identified from field, mainly micrometeorological The Dutch IDEM model (Bleeker et al., 2004; Erisman, 1994)also measurements. These studies have enabled the controlling steps in uses an NH3/SO2 molar ratio as a proxy for surface acidity. For NH3, the deposition pathway to be separated and their response to a range of default Rext values are used for 3 classes of the N/S ratio (very environmental variables quantified. In turn the data and responses low, low and high), depending on surface wetness, land-use and time have been used to develop process-based models and applied to 1 of day, while for SO2 the only effect implemented is to add 50 s m to quantify regional deposition budgets at country and continental the non-stomatal resistance when the N/S ratio is very low (<0.02). scales. There have been surprises, notably in the last decade. The The large reduction in European SO2 emissions and ambient largest surprise has been the recognition that long term (w1 year) concentrations over the last 25 years, and the relative stagnation in average deposition velocities change with time due to changes NH3 emissions and concentrations in Western Europe over the same in the chemical climatology at the regional scale. Thus a few

1 Fig. 4.4. Modelled (EMEP) dry deposition velocity of SO2 (cm s ) over Europe for 1980 and 2000, taking into account the effect of the change in the SO2/NH3 ratio on the canopy resistance (Fagerli pers com). 5218 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

2.5 HCl HNO 2 3 SO2

1.5

1 Concentration (ppb) 0.5

0 -Sor IE-Dri IT-Col IT-Cas FI-Sod IE-Ca2 IT-BCi IT-Ren FR-Gri FI-Kaa FI-Hyy DE-Kli PL-wet IT-Ro2 DE-Gri IT-SRo PT-Esp SE-Nor SE-Sk2 FR-Pue PT-Mi1 FI-Lom DE-Hai UA-Pet BE-Bra BE-Vie FR-Fon DK-Ris NL-Spe FR-LBr ES-ES1 UK-Gri FR-Lq2 FR-Hes NL-Ca1 DK IT-Amp NL-Loo NL-Hor BE-Lon CH-Lae DE-Tha DE-Hoe IT-MBo DE-Geb CH-Oe1 RU-Fyo UK-ESa DE-Wet DK-Lva CZ-BK1 HU-Bug ES-LMa DE-Meh UK-EBu ES-VDA UK-AMo 4

3.5 )

1 SO2/NH3 - 3 (SO2+HNO3+HCl) / NH3

2.5

2 ratio (ppb ppb 3 1.5

1 Acid/NH 0.5

0 IE-Dri IT-Col IT-Cas FI-Sod FI-Kaa IE-Ca2 IT-BCi IT-Ren FR-Gri DE-Kli FI-Hyy PL-wet IT-Ro2 DE-Gri IT-SRo PT-Esp BE-Bra BE-Vie UA-Pet SE-Nor SE-Sk2 FR-Pue ES-ES1 DE-Hai UK-Gri FI-Lom DK-Ris FR-Fon FR-Hes DE-Tha K-AMo DK-Sor NL-Spe FR-LBr PT-Mi1 FR-Lq2 BE-Lon CH-Lae NL-Hor IT-Amp NL-Ca1 NL-Loo RU-Fyo DE-Geb DE-Wet DK-Lva DE-Hoe CH-Oe1 IT-MBo UK-ESa ES-LMa CZ-BK1 HU-Bug DE-Meh UK-EBu ES-VDA U

Fig. 4.5. Top: Annual mean concentrations of SO2, HNO3 and HCl across the NitroEurope network; Bottom: Annual mean Acid/NH3 molar ratios calculated from SO2 alone or from SO2 þ HNO3 þ HCl.

measurements of SO2 deposition rates to parameterise models will Ozone deposition to external surfaces of vegetation is important not be satisfactory in the long term if emissions of any of the acifi- as a removal pathway for ground level ozone but is of little fying or alkaline gases change. It is necessary therefore to underpin consequence for plant effects. The primary potential for injury to estimates of regional SO2 deposition with measured deposition vegetation, requires stomatal uptake of ozone molecules (Fig. 5.1) fluxes and estimates of the surface resistance to quantify the long- followed by reaction with the internal plant tissue generating term trends. The same logic means that deposition velocities from highly reactive oxidants that interfere with physiological processes one region will not necessarily apply elsewhere. The most important (e.g. Matyssek et al., 2008). As ozone is a strong oxidant, it can also region globally for sulphur emissions and deposition is currently react with leaf cuticles and other external plant surfaces or with East Asia, and China specifically. While the methodologies and volatile compounds emitted by vegetation and non-stomatal ozone models developed in Europe and North America are applicable for deposition is a substantial fraction of the total flux. In addition to measurements of SO2 deposition, the use of parameters deduced in vegetation, ozone molecules may be deposited at any surface Europe or North America are not applicable, and measures fluxes providing a chemical sink or acting as a surface for heterogeneous and surface resistances in these regions are necessary to underpin decomposition (Cape et al., 2009). Quantifying the stomatal uptake the assessments. rates is central to understanding the ozone-induced risk to vegetation, but the non-stomatal deposition needs to be quantified to 5. Ozone correctly partition the total deposition flux. Over terrestrial surfaces ozone, confined within the atmospheric 5.1. Introduction boundary layer, has a relatively short lifetime scale of the order of one day due to dry deposition at the surface (Wesely and Hicks, Ozone is a gaseous, phytotoxic secondary air pollutant with 2000). Thus surface removal represents an important control on the widespread effects on human health, vegetation and materials. It is near-surface ozone concentrations, and is the main cause of diurnal also a greenhouse gas (GHG), third behind CO2 and CH4 in impor- variation in rural areas (Garland and Derwent, 1979). Dry deposition tance. Its deleterious effects on plants pose a large-scale risk to crop constitutes a major term in the global mass balance of tropospheric production and forest vitality in many regions of the Northern ozone, the mean global dry deposition sink calculated with 20 Hemisphere (Fowler et al., 1999; Cape, 2008), which have been chemistry-transport models (CTMs) (1000 Tg y1) clearly exceeding widely studied in Europe and North America (e.g. Hayes et al., 2007; the net stratospheric input (550 Tg y1)(Stevenson et al., 2006). Karnosky et al., 2007), there is also evidence of ozone impacts in Asia, The first measurements of ozone deposition fluxes were made Africa and Latin America (e.g. Ashmore, 2005). in the 1950s using the micrometeorological gradient method D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5219

Fig. 5.1. The sinks for ozone at terrestrial surfaces and processes regulating the exchange.

(Regener, 1957). The earliest investigations were aimed at quanti- (Garland and Derwent, 1979). The first long-term measurements fying the surface sink term of the tropospheric ozone budget. Based showed a seasonal cycle over vegetated surfaces that followed the on these, Galbally (1971) concluded that bulk surface resistance (Rc) growing season of the plants (Colbeck and Harrison, 1985), leading of dry soil and short grass surfaces was approximately 100 s m1. to the assumption that ozone deposition is mainly controlled by These and other pioneering studies (e.g. Turner et al., 1974) showed stomatal uptake and deposition to non-vegetated surfaces is that vegetation and soil constitute important pathways by which constant, only depending on the material and surface area. More ozone is removed from the atmosphere, while water and snow recent studies have shown that although deposition rates are partly surfaces are rather inefficient sinks. However, the early studies governed by stomatal uptake over a plant canopy, it only accounts provide rather little information about the processes that control for ca 40–60% of total deposition on average and that the non- ozone deposition to terrestrial or marine surfaces. stomatal component is not constant (Fowler et al., 2001a; Coyle There has also been an interest in measuring surface fluxes et al., 2009; Hogg et al., 2007). These observations are described in prompted by ecological concerns. The importance of environ- more detail in the following sections. mental conditions on plant injury due to ozone through the regulation of stomatal uptake was recognised in 1960s by Mukammal 5.2.1. European forests (1965), who observed that the presence of high concentrations was Ozone deposition fluxes to forests, as well as other vegetated not a sufficient condition for plant injury. Indeed, a few years later surfaces, are largely controlled by the physiological activity and the close coupling between ozone and water vapour fluxes was associated gas exchange of the vegetation, with solar radiation, air demonstrated by Rich et al. (1970). However, while ozone effects on temperature, air humidity and soil moisture as the main controlling vegetation have been closely associated with stomatal uptake for variables. Thus the deposition velocities (Vd) observed above forests decades, only recently have practical risk assessment methods been typically exhibit diurnal and seasonal cycles that depend on the formulated in terms of stomatal uptake rather than ambient structure, physiological responses and phenological state of the trees. concentration (UNECE, 2004). According to present understanding, however, there are other signif- Micrometeorological techniques have been in use since the icant processes in addition to stomatal regulation of gas exchange that first flux measurements. In the late 1970s, Eastman and Stedman control the magnitude and variation of the ozone deposition efficiency (1977) developed a fast-response ozone sensor that facilitated of forests (Altimir et al., 2006; Cieslik, 2004; Dorsey et al., 2004; direct ozone flux density measurements by the eddy covariance Goldstein et al., 2004; Hogg et al., 2007; Lamaud et al., 2002; Tuovi- method. This resulted in a series of measurement campaigns in nen, 2000; Tuovinen et al., 2008a; Zhang et al., 2002). the eastern United States, including various vegetated and The temporal patterns are clearly demonstrated by the long- other surface types (Wesely, 1983). These studies improved the term flux measurement data available from a few sites, such as understanding of deposition processes and formed the basis for those reported for a temperate spruce forest by Mikkelsen et al. the detailed surface resistance parameterisation of Wesely (2004) and a boreal pine forest by Keronen et al. (2003) and Altimir (1989). This parameterisation has been implemented into et al. (2006). In the boreal region in winter, the dormancy of numerous CTMs. In Europe, the eddy covariance technique was vegetation and below-zero temperatures result in low and rela- 1 adopted somewhat later, but rapidly became popular with the tively stable deposition rates (Vd z 0.1 cm s , Fig. 5.2a), while the introduction of a commercial fast-response ozone sensor mean diurnal cycle at the temperate forest shows a weak midday (Gu¨ sten et al., 1992). enhancement related to gas exchange superimposed on a relatively 1 high and seasonally invariable base level (Vd z 0.5 cm s ). The 5.2. Deposition rates decrease of Rc in spring correlates with the onset of photosynthesis, and a well-defined, symmetrical diurnal cycle ensues in summer, 1 Early estimates of ozone dry deposition were obtained from with a Vd maximum of 0.7–0.9 cm s (Keronen et al., 2003; Mik- measurements of the diurnal cycle of ozone in rural areas kelsen et al., 2004). However, Altimir et al. (2006) observed that the 5220 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

a Boreal Pine Forest Median b Temperate Oak Forest 0.7 Winter (Nov-Feb) 1.4 0.6 Summer (May-July) 1.2 July-Aug ] 0.5 ] 1.0 -1 0.4 -1 0.8 0.3 0.6 [cm s [cm s [cm d d

v 0.2 0.4 v 0.1 0.2 0.0 0.0 00 :00 02 :00 04 :00 06 :00 08 :00 10 :00 12 :00 14 :00 16 :00 18 :00 20 :00 22 :00 00 :00 01 :00 03 :00 05 :00 07 :00 09 :00 11 :00 13 :00 15 :00 17 :00 19 :00 21 :00 23 :00 c Potatoes d Temperate Grassland 1.4 0.7 1.2 July-Aug 0.6 Apr-Sep ] ]

-1 1.0 0.5 Oct-Mar -1 0.8 0.4 0.6 0.3 [cm s [ cm s d d 0.4 0.2 v v 0.2 0.1 0.0 0.0 01:00 03:00 05:00 07:00 09:00 11:00 13:00 15:00 17:00 19:00 21:00 23:00 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00

Fig. 5.2. Median diurnal cycles in deposition velocity at (a) boreal scots pine forest, Hyytiala, Finland, 2002–2003 (Altimir et al., 2006), (b) oak forest, Alice Holt, England, 16th July-05–18th August-05 (Coyle et al., 2006), (c) potatoes, Gilchriston, Scotland, 9th July-06–3rd Aug-06, (Coyle et al., 2009) (d) intensively managed lolium perene grassland, Easter Bush Scotland, 2002–2003 (Coyle, 2005). correlation with physiological activity is poorer in autumn and occurrence and persistence of drought. For example, in August concluded that the deposition rate is modified by the frequent 2003 the mean Gst derived for the Italian oak forest by Gerosa et al. wetting of the forest canopy. Both Mikkelsen et al. (2004) and (2008) was only 35% of that in the cooler and wetter August of Altimir et al. (2006) attribute a major part of the total annual ozone 2004, and the effect of drought persisted even after soil water was deposition to non-stomatal pathways. replenished by rainfall. High non-stomatal fluxes are also observed in Mediterranean forests (Gerosa et al., 2005, 2008). However, the diurnal and 5.2.2. Crops seasonal variations differ from those of the northern forests in many For agricultural crops, ozone deposition rates exhibit pronounced aspects. The measurements above oak forests in central Italy seasonality that results from the distinct phenological stages of the (Gerosa et al., 2005, 2008; Cieslik, 2009) and south-eastern France growing season. The flux measurements above an Italian barley field (Michou et al., 2005) show that dry and hot conditions can signifi- by Gerosa et al. (2004) demonstrate how Vd increases during the first cantly affect the diurnal courses of Vd and Rc. On the other hand, in growth stages (seedling growth, tillering, stem elongation). The this region there is a potential for high deposition rates throughout maximum is reached soon after anthesis, during the grain filling the year, and higher stomatal uptake may take place during winter period, when photosynthetic activity is at its highest level. Gerosa 1 than summer months, in spite of the lower ozone concentrations in et al. (2004) observed an average Rc of about 75 s m for this period, 1 winter (Cieslik, 2009). while the bulk stomatal resistance (Rst) was about 150 s m . After During dry periods stomata are either almost completely closed that, deposition rates decrease gradually with ripening of the crop 1 or the cycle of stomatal conductance (Gst ¼ Rst ) is less symmetrical, and leaf senescence, as Rst increases, and are further reduced by with a rapid increase from the nocturnal levels to a maximum in harvest. A slightly higher minimum Rc but a similar decrease was the morning, rather than around noon, and a gradual decrease observed at the same site for wheat. In this case, the decline was towards the evening. The latter behaviour may take place in more amplified by the rapid drying of soil (Gerosa et al., 2003). northern forests as well, if leaf temperatures reach sufficiently high For both barley and wheat, the diurnal cycles of Vd and surface levels (e.g. Dorsey et al., 2004; Tuovinen et al., 2008a). At the French conductances were symmetrical during the photosynthetically 1 site, Vd starts increasing very early (at 3–4 a.m. local time) and it active period with a maximum (Vd z 0.7–0.9 cm s ) around noon was suggested that this could be related to either stomatal response (Gerosa et al., 2003, 2004). During the latter part of the growing to blue light, resulting in uptake already in the predawn hours, or to season, the midday deposition rates are strongly reduced, due to non-stomatal deposition enhanced by surface wetness (Michou increased Rst, resulting in an earlier maximum and a diurnal course et al., 2005). At the Italian site, however, the maximum (in Gst) that is skewed towards morning. In the afternoon, values compa- occurs later and seems to have a non-stomatal origin, possibly due rable to those after harvest were observed for the barley field to the reaction with the NO accumulated within the forest canopy (Gerosa et al., 2004). (Gerosa et al., 2005) or leaf wetness (Gerosa et al., 2008). Similarly, For other crops, data are rather limited. Michou et al. (2005) the measurements taken by Coyle et al. (2006) in an oak forest report a symmetrical diurnal cycle for the Vd measured over in England in summer show a steep increase to the maximum at a rapidly growing maize field, with a mean minimum of 0.05 cm s1 1 1 8 a.m. (Vd z 1.0 cm s ) and a approximately linear decrease to and a mean maximum of 0.50 cm s . In an earlier North American 1 a nocturnal level (Vd z 0.1 cm s ), Fig. 5.2b. study, a similar diurnal cycle, with slightly higher values throughout In addition to the phenological development of plants, the the day, was observed over a maize field during the period of most seasonal cycle can be strongly influenced by the soil moisture active growth (Meyers et al., 1998). During senescence, the hourly 1 conditions, especially in southern Europe. Consequently, there may mean Vd only reached 0.2 cm s in the morning. The patterns were be large annual variations in ozone uptake rates depending on the also similar for soybean, but the Rc of soybean seems to be D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5221 significantly lower than that of maize, as the maximum mean primary productivity at modest O3 exposure concentrations 1 hourly Vd was almost 1 cm s during the active growth period (King et al., 2005). (Meyers et al., 1998). Coyle et al. (2009) reported an asymmetrical diurnal cycle in Vd over a potato field during the phase of tuber 5.2.4. Other vegetated surfaces initiation and growth through to harvest, with a median value of Measurements have been made over a variety of other plant 0.6 cm s1, day-time values from 0.5 to 2 cm s1 decreasing to canopies from moorlands and subartic mires to tropical forests. They 0.4 cm s1, or less, at night (Fig. 5.2c). all exhibit diurnal and seasonal cycles driven by variations in As was the case with forests, stomatal uptake rates derived from stomatal activity and climate, as described for the previous canopies. the evapotranspiration fluxes only explain a part of the total ozone For example Fowler et al. (2001) for moorland reported summer flux and a significant proportion must be attributed to non-stomatal diurnal cycles ranging from w0.3 cm s1 at night to w0.6 cm s1 sinks. Even during the active growth period, no more than 50–60% during the day while in the winter the afternoon peak was only of the total flux to a wheat field was stomatal, and this fraction w0.4 cm s1 with night-time values also w0.3 cm s1. Tuovinen et al. decreased during the senescence (Gerosa et al., 2003). The same was (1998) measured a small diurnal cycle over flark fen, 300 km north of true for barley, and even though the day-to-day variation in the the Artic circle in the late summer, ranging from 0.1 to 0.15 cm s1 at inferred non-stomatal flux fraction is large, the corresponding non- night to only w0.2 cm s1 during the day. For tropical forests there stomatal surface conductance remains relatively stable throughout are often two seasons, wet and dry: During the wet season, Rummel the summer (Gerosa et al., 2004). Similar results were obtained for et al. (2007) reported diurnal cycles over Amazonian rain forest onion, but in this case the variation can be explained by irrigation ranging from w0.4 cm s1 during the night to w1cms1 at day, with that clearly enhanced both stomatal and total fluxes (Cieslik, 2009). a symmetrical diurnal cycle. In the case of potatoes, the non-stomatal component was only w15% when the canopy was well-watered but increased to w80% when the 5.2.5. Non-vegetated surfaces crop became senescent. (Coyle et al., 2009). Deposition to the soil underlying the vegetation layer may significantly contribute to the vertical ozone flux observed above the canopy 5.2.3. Grasslands (e.g. Dorsey et al., 2004). Especially in arid regions, the surface resis- Grasslands can be used to describe a wide variety of habitats tance of soil (Rsoil) is the key determinant of the surface removal of from intensively managed pastures that are usually dominated by ozone (e.g. Michou et al., 2005). As the literature review by Massman a single species, such as Lolium perenne, to natural grasslands which (2004) and the more recent data of Sorimachi and Sakamoto (2007) 1 contain a rich diversity of grasses, forbs and legumes and are often indicate, Rsoil is highly variable, ranging from 10 to >1000 s m .Ithas of high conservation value. The canopies that have been studied to been observed that Rsoil decreases with increasing organic content date all exhibit similar patterns of deposition as forests and agri- and porosity of soil. Clearly, wet soils have a considerably higher Rsoil cultural crops in that they have phenologically driven seasonal and (w500 s m1) than dry soils (w100 s m1)(Galbally and Roy, 1980; diurnal cycles. There are few long-term measurements of ozone Massman, 2004), as increasing the moisture content of soil decreases deposition to grasslands reported in the literature at present its porosity and thus reduces the area of reactive surface available to (Colbeck and Harrison, 1985; Gru¨ nhage and Ja¨ger, 1994; Pio et al., ozone molecules (Sorimachi and Sakamoto, 2007). However, it is 2000). All these studies measured during winter and summer so difficult to disentangle individual effects based on the current data, and that the growing season and dormant periods were observed. The the situation is further complicated by biogenic NO emissions from results of several short-term campaigns over active and dormant or soils. Removal through the reaction with NO potentially constitutes dry grasslands have also been reported and are summarized below a significant sink for ozone, especially in forests at night (Pilegaard, (Bassin et al., 2004; Garland and Derwent, 1979; Meyers et al., 1998; 2001; Dorsey et al., 2004), even though this reaction does not take Sorimachi et al., 2003). place specifically at the air–soil interface. 1 Over active, green grasslands the daytime Vd is only 0.5 cm s on average, decreasing to w0.1–0.2 cm s1 at night, although peaks 5.2.5.1. Snow. The dry deposition velocity over snow- and ice- over 1 cm s1 are often observed (Fig. 5.2d). The diurnal cycle is covered surfaces and water is known to be smaller than 1 mm s1. often symmetrical with a steady increase in the morning after However, the measurement data are highly variable. It is possible sunrise and decrease is the afternoon as light and temperatures that the measured Vd is affected by chemical reactions taking place decrease. However (Gru¨ nhage and Ja¨ger, 1994) reported an asy- in the snowpack, which, combined with dynamic transport metrical diurnal cycle in Vd with a steep increase after 6 a.m. until 9 processes, can result in the observed variability. Helmig et al. a.m. when it steadily declined. This is attributed to an increase in (2007) modelled ozone concentrations in high northern latitudes water vapour pressure deficit (VPD) at midday and the afternoon with different values of Rc and demonstrated how even small causing stomata to close, as has been observed for many other deposition rates, if effective over large areas, can significantly affect canopies. Where measurements have been made over dormant the near-surface concentrations and that a high Rc is required for (i.e. during winter) or dry grasslands the diurnal cycle is far less snow in order to reproduce the observed concentrations; the best 1 1 pronounced with daytime Vd only reaching w0.2 cm s although agreement was obtained when limiting Vd to 0.01 cm s . night-time values are similar at all times of year (Fig. 5.2d). Coyle, (2005) showed that non-stomatal uptake was w60% of 5.2.5.2. Water. For water surfaces, current understanding of the total budget over an improved grassland in Central Scotland. controlling processes is more coherent, involving both turbulent and Pleijel et al. (1995) found that the non-stomatal sink is enhanced by molecular mixing, and chemical reactions. It has been observed that surface wetness while the work of Coyle (2005) also demonstrated wind-induced turbulence greatly enhances deposition rates by that the non-stomatal component was not constant but varied with increasing atmospheric mixing, surface roughness, wave breaking wetness, surface temperature, solar radiation and wind speed as and spray generation (e.g. Gallagher et al., 2001). The observations of 1 has been suggested for other canopies. Rc range from 1000 to 10,000 s m (Gallagher et al., 2001). At low Ozone deposition to forests has also been extensively studied in wind speeds, Vd increasingly depends on the molecular gas transfer North America, and in recent years a unique study in elevated CO2 near the air–water interface. Even in the absence of turbulence, using a Free Air Enrichment Experiment (FACE) has demonstrated significant deposition rates are possible, since the chemical reactions strong interactions between O3 and CO2, the former decreasing taking place in the aqueous phase enable more efficient deposition 5222 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 than the solubility of ozone alone would suggest. The modelling logarithm of the surface resistance in s m1 is taken as the inverse results of Fairall et al. (2007) show that the oceanic turbulent mixing reaction rate). The results for four vegetated canopies are also plotted also plays an important role in enhancing ozone deposition by up to in Fig. 5.3 and the slope of their linear regression lines is of the afactorofthree.Iodide(Chang et al., 2004) and chlorophyll (Clifford same order of magnitude as the artificial surfaces. This shows that the et al., 2008) have been suggested as the main reagents controlling dependence on temperature and activation energies are similar for all ozone destruction in the organic surface microlayer. As the distri- surfaces but the absolute reaction rates differ. The simplest conclusion bution of these compounds in water bodies is related to that of is that heterogeneous decomposition of ozone to molecular oxygen is phytoplankton, the chemical enhancement of ozone deposition can the underlying process responsible; hence the similar activation be expected to be highly variable both temporally and spatially. energies in Fig. 5.3 andthevariationinreactionratescanbeattributed Similarly, coastal ozone deposition to the iodide-rich macroalgae to differences in effective surface area (Cape et al., 2009). surfaces depends on the tidal phase, and fluxes can be further Cape et al. (2009) also tested the hypothesis that the surface enhanced by photochemical destruction of ozone during the iodine- reactivity of vegetation may be enhanced by reaction of biogenic mediated particle formation events (Whitehead et al., 2009). volatile organic compounds (BVOCs) dissolved in cuticular waxes and showed no enhancement due to surface reaction. However, 5.3. Non-stomatal deposition processes ozone does react in the gase phase with BVOCs emitted by vegetation, with gas-phase reaction rate coefficients varying between Although the stomatal uptake of ozone is an important sink over 1018 and 1016 cm3 molec1 s1, potentially leading to apparent vegetated surfaces it accounts for only a fraction (typically 1/3–2/3) of non-stomatal deposition velocities of similar magnitude to those the total deposition. In most studies it has been assumed that the measured in the field (Coyle, 2005). The emission of BVOCs by non-stomatal sink is constant, depending only on the surface mate- vegetation is also light and temperature dependent, increasing rial and area, although it was expected that the presence of surface with both parameters which may explain some of the variation in water would inhibit deposition as the solubility of ozone is quite non-stomatal deposition. Nevertheless, most measurements indi- small. However, field measurements have indicated that surface cate that the concentrations or reactivity of the emitted BVOCs are temperature, solar radiation, surface wetness and wind speed may all not sufficient to explain the magnitude or variation in non-stomatal influence the magnitude of the non-stomatal flux. The influence of deposition in all circumstances. In can be concluded that although wind speed is simply explained, as when wind speed increases more BVOCs may play a part in the non-stomatal deposition they are only air will penetrate the canopy, increasing the surface area available for significant for species that emit currently unidentified compounds deposition. The mechanisms that have been proposed for the other that react very rapidly with ozone (Hogg et al., 2007). parameters are: Although some studies have shown surface water inhibits ozone deposition to a vegetated canopy the consensus is now that C Temperature: thermal decomposition ozone on plant surfaces, it increases deposition (Hogg et al., 2007; Coyle et al., 2008a)in mediated by waxes and other substances on the surface most circumstances. Although Fuentes (1992) found more organic (Coyle et al., 2009; Hogg et al., 2007;Fowleretal.,2001;Cape compounds in water from maple leaves compared to poplar, specific et al., 2009) compounds that may be responsible have not been identified. C Solar radiation: ozone photolysis also mediated by the surface Coyle et al., (2009) suggested that non-stomatal deposition is gov- (Coyle et al., 2009; Hogg et al., 2007 and references therein) erned by three main regimes: ozone deposition increasing as the and reaction with VOCs emitted by vegetation (Hogg et al., temperature and solar radiation increases on a dry surface due to 2007; Coyle, 2005) thermal decomposition; decreased deposition on surfaces with C Surface wetness: aqueous reactions in water-films on plant a thin film of water present as thermal decomposition is blocked by surfaces (Coyle et al., 2009; Altimir et al.,) the water film; enhanced deposition on a fully wetted surface due to aqueous reactions in the water. Principal component analysis of data from several field While non-stomatal deposition has become widely recognised campaigns indicated the following order of precedence: tempera- as an important sink, the concept of stomatal uptake at night is less ture, surface wetness (measured as vapour pressure), solar radia- widely appreciated and this complicates the simplistic view of day– tion then wind speed although for forests temperature and wetness night differences in ozone sinks in vegetation (Grulke et al., 2004). were of almost equal importance (Coyle et al., 2008a). Some preliminary work exposing wax coated and metal surfaces to 5.4. Model development and validation ozone in controlled environment chambers (Cape et al., 2009)showed that Vd is temperature dependent. An Arrhenius analysis of the change The recent European measurement data on ozone fluxes have in reaction rate with temperature is shown in Fig. 5.3 (the natural been used for testing and improving the DO3SE deposition

14 stainless steel y = 40.1x - 3.28, R2 = 0.84 aluminium foil y = 24.9x + 0.14, R2 = 0.29 12 paraffin wax y = 22.8x + 0.85, R2 = 0.18 10 beeswax y = 16.1x + 2.18, R2 = 0.44 moorland vegetation y = 36.4x - 9.62, R2 = 1

ln(Rns) 8 Potatoes y = 49.9x - 14.84, R2 = 0.06 6 Grassland y = 52.6x - 16.26, R2 = 0.06 Forests y = 56.2x - 16.56, R2 = 0.14 4 0.39 0.4 0.41 0.42 0.43 1000/RT

Fig. 5.3. Arrenhius relationship analyses for ozone deposition to various surfaces: stainless steel, Aluminium foil, paraffin wax and beeswax from Cape et al. (2009); moorland Fowler et al. (2001); potatoes Coyle et al. (2009); Grassland and Forests, Coyle et al. (2008a). D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5223 module, which has been incorporated into the Unified EMEP CTM AOT40 is still the most common risk indicator used in Europe for developed for European policy-making applications (Tuovinen setting environmental objectives and defining the so-called critical et al., 2001, 2004, 2008b; Emberson et al., 2007). DO3SE makes it levels, Ashmore and Fuhrer (2000). For a proper application of AOT40, possible to calculate stomatal and non-stomatal ozone fluxes to ozone concentration must be known at the height of the canopy different vegetation types, taking into account both plant top (UNECE, 2004). This means that the concentration determined phenological and meteorological factors (irradiance, temperature, above this height (as is typically the case with measurements) must humidity, soil moisture) on an hourly basis (Simpson et al., 2007; be transformed to the correct reference height, because of the Emberson et al., 2000, 2007). Many of the validation studies deposition-sink generated vertical concentration gradient; a failure have been focussed on the leaf-scale stomatal conductance of to correct for this gradient may seriously overestimate the risk a specific plant species only, since parameterisations of this kind are metrics (Tuovinen and Simpson, 2008b). Even if the profile correction needed to relate the ozone uptake to plant response (e.g. Pleijel compensates for a significant bias, the near-surface concentration et al., 2007). There are also smaller-scale CTMs covering a part of may prove a poor surrogate for the effect-inducing flux. High ozone Europe, which have been used for high-resolution mapping of ozone concentrations are frequently connected with conditions that poten- fluxes (e.g. Lagzi et al., 2004), and local-scale soil–vegetation– tially limit the stomatal uptake, such as high temperature and VPD atmosphere-transfer models that include ozone (e.g. Gru¨ nhage and (e.g. Solberg et al., 2008). This co-variation means that the concen- Haenel, 2008). Inferential modelling (IM) has been used for tration at leaf surface is not necessarily connected with a proportional calculating regional ozone budgets (Coyle et al., 2003) and mapping stomatal uptake and therefore plant response (Cieslik, 2004). This is exposures and doses on a high (1–2-km) spatial resolution for one reason for the different accumulation rates of AOT40 and stomatal national-scale risk assessment of ozone effects (e.g. Keller et al., uptake observed in many studies (Fig. 5.4). 2007). As a compromise between the less data demanding exposure The global-scale CTMs (Stevenson et al., 2006), as well as many indices and the more realistic dose metrics, solutions based on an regional models (e.g. Vautard et al., 2005), typically include a variant ‘effective’ concentration have been suggested (e.g. Gerosa et al., of the parameterisation of Wesely (1989). This parameterisation 2004; Karlsson et al., 2004; Pleijel et al., 2004). Common to all these does not include the stomatal effect of soil moisture conditions, is the idea that the concentrations for AOTX are first modified to which has been shown to be a significant modifier of ozone fluxes, accommodate environmental factors controlling stomatal uptake, especially in the Mediterranean region (Gerosa et al., 2008), yet such as VPD in the definition of the modified AOT30. In some cases, proved challenging to model within CTMs (Emberson et al., 2007). all the main modifiers, such as those in the DO3SE model, are Another key problem with large-scale CTMs is related to the aggre- considered (Gerosa et al., 2004; Pleijel et al., 2004). However, this gated land cover classes, making it difficult to parameterise sub-grid processes. For example, the dry deposition module of the recently developed global Modular Earth Submodel System (MESSy) does not differentiate between different vegetation types, even though a soil moisture stress function is included (Kerkeweg et al., 2006). The non-stomatal deposition processes are parameterised in CTMs and IM systems in a much simpler way than the stomatal component, typically by defining constant values for the relevant resistances. However, a preliminary parameterisation has been developed for the EMEP CTM for surface wetness effects for northern European coniferous forests (Tuovinen et al., 2008). This parameterisation is derived from the observations of Altimir et al. (2006) and represents a gradual increase in the surface sink with increasing surface wetness, parameterised as a function of relative humidity. This results in higher and more variable ozone removal rates within the model. In the future, integrated models are needed to couple the surface exchange of energy, carbon and trace gases. In particular, a multi-layer structure facilitating an explicit simulation of vertical mixing and other in-canopy processes would be useful for interpreting flux measurements (e.g. Duyzer et al., 2004; Simon et al., 2005a).

5.5. Risk assessment methods

European abatement strategies are founded on effects-based approaches, which involves different numerical indicators for different air pollution effects on vegetation and human health (UNECE, 2004). For potential ozone effects on vegetation, the AOTX (Accumulated exposure Over a Threshold of X ppb) exposure index replaced simpler concentration averages in the 1990s (Fuhrer et al., 1997). Present definitions also include a metric based on the stomatal uptake flux, AFstY (Accumulated stomatal 2 1 flux Fst above a threshold of Y nmol m s ), which represents the absorbed dose and is thus considered biologically more meaningful than the concentration-based AOTX (UNECE, 2004). AFstY is more complex than AOTX in that it entails modelling the Fig. 5.4. Accumulation of AOT40 and stomatal dose over a Holm oak forest (6 August–11 stomatal conductance. October) in 2003 and 2004 in Italy (Gerosa et al., 2008). 5224 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 approach is very close to actually calculating the stomatal flux, as it changes in the meteorological input data. This resulted in involves a multiplicative stomatal conductance model. Even the a decreased dry deposition sink, which increased the near-surface profile corrections required for AOTX are based on flux–gradient ozone concentrations by 2–8 ppb on a seasonal basis. However, relationships of ozone and thus entail deposition modelling (Tuo- a reduction in Gst, due to increased CO2 or any other effect, does not vinen and Simpson, 2008b). From a micrometeorological point of proportionally reduce the stomatal uptake flux. This results from the view, it would thus appear natural to aim at developing accurate effect of decreased surface removal on the overall mass balance, with parameterisations for partitioning the total ozone flux into the higher concentrations partly compensating for the suppressed Gst. stomatal and non-stomatal components and applying flux-based While it would seem plausible that in warm climates increasing risk metrics because of their superior biological basis. temperatures reduce stomatal exchange, the opposite is true for The model calculations of Simpson et al. (2007) indicate that cooler regions. However, based on a modified version of the DO3SE AOT40 and AFstY (for both crops and forests) show very different model, Karlsson et al. (2007) concluded that in northern Scandinavia regional patterns of exceedance of critical levels across Europe with the most significant impact of the higher temperatures may be much smaller south–north gradients and larger exceedance area related to an earlier onset of the growing season and the associated for AFstY (Fig. 5.5). Even though there are still numerous uncer- phenological development, rather than their direct enhancement of tainties involved in this kind of modelling, there is evidence that Gst. This together with elevated and increasing ozone concentrations the flux-based risk maps better correlate with observed plant in spring may amplify the risk of negative ozone effects on vegeta- damage (Hayes et al., 2007). tion in these areas. On the other hand, there may be a counteracting effect on the stomatal uptake mediated by the concurrent higher 5.6. Potential effects of climate change VPD (Karlsson et al., 2007; Harmens et al., 2007). The summer of 2003 was exceptionally warm in Europe, espe- Changes in the climatic conditions and chemical composition of the cially in the central part of the continent, and may be taken as an atmosphereareexpectedtohaveawiderangeofeffectsonthe analogue of the future summers to be expected in the latter part of interactions between tropospheric ozone and the biosphere. First, the 21st century. A series of heat waves produced meteorological ozone exposures are changing globally due to changes in precursor conditions highly favourable for the net formation of ozone and its emissions. Second, the long-term changes in meteorological condi- build-up over large areas; indeed, record-high near-surface concen- tions affect atmospheric transport patterns and the rates of tropo- trations were observed in many locations (Solberg et al., 2008). It is spheric chemical reactions and dry deposition processes, and also very likely that reduced dry deposition played a significant role in the modify plant phenology. In addition to the rising temperature and formation of the ozone episodes in 2003. The high temperatures and changes in precipitation distribution, elevated CO2 and ozone soil moisture deficits (SMDs) most probably decreased the Gst of concentrations may act as significant modifiers to stomatal exchange vegetation and thus ozone removal from the atmosphere in central (e.g. Ashmore, 2005). Finally, the characteristics of vegetation cover and southern Europe, as indicated by the Italian eddy covariance and land use may be altered on various scales as a result of human measurements (Gerosa et al., 2008) discussed above. Fig. 5.4 shows activities, effects of climate and ozone on plant species composition that the ozone dose absorbed by a Holm oak forest in August– and ecosystem function, and natural disturbances, all of which September 2003 was less than 50% of that during the same period in potentially generate feedbacks to the surface removal of ozone. 2004, in spite of the much higher concentrations in 2003. So far, few studies have addressed the projected changes beyond The sensitivity runs with a global CTM by Solberg et al. (2008) the ozone precursor emissions and atmospheric dynamics. In the demonstrate the potentially large effect of dry deposition on near- multi-model ensemble simulations of future concentrations by surface concentrations. Similarly, doubling of Rc within the model- Stevenson et al. (2006), the projected Vd was only altered by the ling study of Vautard et al. (2005), partly because of the expected meteorological responses, neglecting the effects of water stress and increase in SMD which is not taken into account in the deposition elevated CO2 concentrations, for example. In some studies, indi- parameterisation, improved the model performance by increasing vidual, uncoupled effects have been included in the models. For the modelled concentrations. Considering the accumulation of example, Sanderson et al. (2007) investigated the impact of the ozone dose of plants over the whole growing season, the significance stomatal conductance changes as directly induced by the rising CO2 of drought periods much depends on their timing with respect to the levels. In this experiment, a global CTM was run with an assumed phenological stage of plants and the occurrence of elevated ozone reduction in Gst due to a doubling of CO2 concentrations, but with no concentrations (Harmens et al., 2007). In addition, prolonged

Fig. 5.5. Ratio of the AOT40 (left) and AFst1.6 (right) risk metric to the corresponding critical level for forests (not shown for values < 1) (Simpson et al., 2007). D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5225 drought stress may result in sustained impairment of the hydraulic 6.1.2. Oxygenated volatile compounds conductivity of plants, challenging the traditional dry deposition While the production and emission of volatile isoprenoids, and models (Gerosa et al., 2008). in particular isoprene and monoterpenes, is strongly species- It has been estimated that exposure of plants to even the current specific, all plants emit oxygenated volatiles. At the global scale, the levels of ozone may significantly increase water use of forest trees emission source strength of these compounds is generally smaller (McLaughlin et al., 2007) and reduce plant productivity in the most than that for volatile isoprenoids, and many of these oxygenated polluted areas of the world, with exacerbating effects projected for compounds are less reactive than isoprenoids in the atmosphere. the future (Felzer et al., 2005). With elevated ozone concentrations, However, the emissions of oxygenated compounds, which may the reductions in carbon sequestration may also lower soil carbon be induced by developmental and stress factors, may be large at formation rates and alter the below-ground carbon cycling (Loya certain periods of the year and by certain vegetation types (see also et al., 2003). Sitch et al. (2007) suggest that the ozone-induced flux measurements below). suppression of the global land-carbon sink gives rise to additional Methanol, acetaldehyde and C-6 compounds are often emitted in accumulation of anthropogenic CO2 emissions in the atmosphere large quantities, especially in the presence of mechanical wounding and thus should be considered an indirect radiative forcing, which or other stresses (Loreto et al., 2006). Methanol formation is prob- could exceed the direct radiative forcing due to ozone increases. ably due to the demethylation of pectins in cell walls (Galbally and Kirstine, 2002) and does not have any known protective role for plants. The release of methanol into the atmosphere is therefore 6. Biogenic volatile organic compounds (BVOC) associated with cell wall damage occurring because of wounding (Karl et al., 2001a). Methanol is also emitted by growing plant tissues 6.1. Introduction (Nemecek-Marshall et al., 1995; Harley et al., 2007; Hu¨ ve et al., 2007), and senescing tissues (Fall, 2003). Large fluxes of methanol Biogenic volatile organic compounds (BVOC) are emitted by could be measured, as an example, from rapidly expanding leaves of almost all plants. In higher plants, emissions range from close to zero the Mediterranean vegetation during the spring ACCENT–VOCBAS to 10–20% of the carbon fixed by photosynthesis. Global emissions 2007 campaign (see below). have been estimated at around 800 Tg C y1 although this figure Large fluxes of acetaldehyde have been observed in conditions has been regularly revised based on improvements in scaling up of of root anoxia such as under waterlogging stress. Short-lived bursts laboratory results, spatial and temporal integrations, and large-scale of acetaldehyde are sometimes also observed from darkened leaves monitoring at whole ecosystem levels (Lathiere et al., 2006; Arneth (Karl et al., 2002b). Interestingly, acetaldehyde is also emitted et al., in press). Approximately half of the emissions are believed to following wounding (Fall et al., 1999) and ozone stress episodes, be isoprene (Guenther et al., 2000, 2006). Monoterpenes, the other and large fluxes of this compound can be observed under natural large class of volatile isoprenoids, contribute another 10–15% of the conditions (Lathiere et al., 2006). total BVOC emissions. Sesquiterpenes, a third class of isoprenoids, Finally, C-6 oxygenated compounds are emitted from leaves are emitted in small quantities from non-stressed vegetation, except subject to various stresses such as wounding, e.g. as a consequence of from flowers. The remainder is emitted as oxygenated volatile cutting hay, insect feeding, ozone stress and heat stress (Hatanaka, compounds, including alcohols, aldehydes and ketones, particularly 1993). Aldehydes, (Z)-3-hexenal, (E)-3-hexenal and (E)-2-hexenal during periods of plant development or in response to environ- with characteristic green leaf (‘cut grass’) odour are formed first, mental stress (Heiden et al., 2003; Seco et al., 2007). and then transformed into corresponding alcohols by alcohol dehydrogenases. Esters such as hexenolacetates can also be formed 6.1.1. Volatile isoprenoids and emitted during these processes. Proton-transfer reaction mass- Volatile isoprenoids have been extensively studied compounds spectrometry has provided detailed insight into the associated because of their relevant functions in plant vs. environment inter- time-sequence of events (Beauchamp et al., 2005). actions and their role in the atmosphere. Isoprene and monoterpenes are formed in plastids via methylerythritol phosphate (MEP) pathway (Lichtenthaler, 1999). 6.2. Environmental controls on BVOC emissions While isoprenoid emissions mainly rely on newly synthesized photosynthetic metabolites in chloroplasts, extra-chloroplastic 6.2.1. Physiological and physico-chemical controls of emissions sources can feed carbon to sustain isoprene or monoterpene Models of BVOC emissions consider that emissions are controlled biosynthesis, including xylem-transported sugars and chloroplastic either by physiological factors (‘‘isoprene’’ algorithm) or by physico- starch (Karl et al., 2002a; Kreuzwieser et al., 2002)aswellas chemical factors (‘‘monoterpene’’ algorithm) (Guenther et al., refixation of respired CO2 (Loreto et al., 2004). These additional 1993). By considering only physiological factors, the synthesized carbon sources of isoprenoid biosynthesis can become significant compounds are immediately released from the foliage. In contrast, especially when photosynthesis is constrained by environmental by considering only physico-chemical factors, the compounds are stresses. Under extreme stress conditions, such as drought stress, emitted from specialized storage structures such as resin ducts the leaf carbon budget can become negative, as leaves release more present in conifers, glandular trichomes in species from Lamiaceae carbon in the form of isoprenoids and respiratory CO2 than they (peppermint), and oil glands in Rutaceae (lemon, orange) and gain through photosynthesis (e.g. Brilli et al., 2007; Schnitzler et al., Myrtaceae (eucalypts). 2004). Physiological controls operate at the level of compound Monoterpenes and sesquiterpenes are active compounds in plant synthesis. Light and temperature, the key environmental drivers, interactions with other organisms. Monoterpenes may either attract affect the rate of intermediate production; temperature also affects or deter herbivores or carnivores, and attract pollinators (Gershenzon the activity of flux controlling enzymes (Fig. 6.1, Niinemets et al., and Dudareva, 2007). Indirect evidence suggests that isoprene 1999) Over the longer term, synthesis and turnover of rate-limiting and monoterpenes as lipid-soluble molecules may protect plant enzymes can control the flux rate (Monson et al., 1994; Lehning membranes from thermal and oxidative stress (reviewed by Sharkey et al., 2001; Fischbach et al., 2002). In species with large storage and Yeh, 2001). This favourable action can also assist in adapting pools, the emissions can be independent of the rate of compound isoprenoid-emitters to increasing oxidative pressures (Lerdau, 2007). synthesis, being controlled by temperature effects on the 5226 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

Fig. 6.1. The emission of volatile organic compounds from plants is limited by both physiological and physico-chemical characteristics. Physiological factors control the rate of synthesis of VOC and operate at the level of intermediate production and the activity of flux controlling enzymes such as isoprene synthase or terpene synthases for volatile isoprenoids. Physico-chemical factors, in particular, low compound volatility and rate of diffusion, can limit the release of synthesized VOC from the leaves and determine the degree to which the synthesized compound can be stored in the leaves. evaporation and diffusion of compounds from the storage pools concentration and atmospheric reactivity in morning hours. Current (Fig. 6.1, e.g. Tingey et al., 1991). steady-state models predict zero nightime monoterpenes emissions Often there is no clear separation between physiological and for species lacking specialized storage structures. physico-chemical controls. Although it is generally belived that only evaporation from pools controls the emissions in species with 6.2.3. Uptake and release of volatile compounds by vegetation specialized storage pools, there is increasing evidence that the A relevant implication of the non-specific storage is the uptake of emissions can be partly controlled by physiological factors also in volatile compounds from ambient air when air concentrations are classical ‘‘storage’’ species. On the other hand, physico-chemical higher than those in equilibrium with plant liquid and lipid phases. controls on emissions often interact with physiological controls in The compounds taken up during the periods with high atmospheric species without specialized storage pools for BVOC (Fig. 6.1). BVOC concentrations may be released back into the ambient air when air concentrations are small if they are not metabolized or 6.2.2. Physico-chemical controls of emission in species lacking translocated to the roots. The uptake of water-soluble compounds specific storage structures is expected to scale with leaf water content, while the uptake of Every BVOC species can be non-specifically stored in leaf liquid lipid-soluble compounds with leaf lipid content (Noe et al., 2008a). and lipid phases, with the non-specific storage capacity depending on Thus, even species considered ‘‘non-emitting’’ can emit several the compound physico-chemical traits such as the gas/liquid aqueous BVOCs at trace level from the non-specific storage built up from phase partition coefficient (Henry’s law constant, H) and lipid/liquid ambient sources. phase partition coefficient (octanol/water partition coefficient, KOW). For instance, compounds that are highly water-soluble such as methanol and ethanol can accumulate in leaf aqueous phase, especially if gas-phase diffusion out of the leaves is hindered due to limited opening of stomatal pores. Although the rate of compound synthesis may respond very quickly to environmental perturbations, a build up of water-soluble compounds reduces the sensitivity of the emission responses to variation in environmental factors. Analyses of the emissions of strongly lipid-soluble BVOC species such as non-oxygenated monoterpenes indicates that the non-specific storage of these compounds, mainly in leaf lipid phase, significantly alters the emission kinetics in species lacking specialized monoterpene storage pools. In these species, to reach steady-state rates of monoterpene emission can take from minutes to hours depending on monoterpene physico-chemical characteristics (Niinemets and Reichstein, 2002; Noe et al., 2006). The delayed emission responses due to non-specific storage can also result in modified sensitivity of the emissions to environmental factors. For instance, a sigmoidal light-response curve can result if non-specific storage pools have not yet reached a steady- state with each light level. Under such experimental conditions, the emission rate recorded is lower than the monoterpene synthesis rate. Given the long time periods, often on the order of 1 h required to reach the steady-state, non-steady-state conditions are common in monoterpene measurements. In addition to alteration of the immediate environmental controls, Fig. 6.2. Monoterpene emissions from Quercus ilex dominated forest in Castelporziano, non-specific storage can modify the emissions at daily and weekly Italy for six days in June simulated using the standard Guenther et al. (1993) model and timescales. Another important implication of the non-specific a model considering non-specific monoterpene storage in leaf liquid and lipid pools storage is significant nocturnal emissions, which was observed e.g. in (modified from Niinemets and Reichstein, 2002; Niinemets, 2008). The standard emis- the case of monoterpenes (Loreto et al., 2000; Niinemets et al., sion model predicts that the emission rate responds immediately to changes in light and temperature, but non-specific storage of lipid-soluble non-oxygenated and water-soluble 2002b). Simulation analyses indicate substantial nocturnal emissions oxygenated monoterpenes results in time-lags between terpene synthesis and emission. at the ecosystem scale (Fig. 6.2). Significant night-time BVOC emis- As the result of these time-lags, the emissions are predicted to continue also at night, sions from non-specific storage can strongly influence OH-radical although synthesis has ceased. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5227

6.2.4. CO2-Dependence of emissions Although the available emission information has been recently The classical Guenther (1993) algorithm considers strong light and collated, data for many key emitting species are still lacking. Recent temperature dependencies of isoprene and ‘‘non-stored’’ mono- observations have indicated that several important species such as terpene emissions. CO2 was not considered as an important factor in cork oak (Quercus suber)(Staudt et al., 2004; Pio et al., 2005) and controlling the emission of volatile isoprenoids. More recent labora- European beech (Fagus sylvatica)(Moukhtar et al., 2005; Holzke tory and field studies have established that volatile isoprenoids are et al., 2006) previously considered non-emitters are moderate to sensitive to ambient CO2 and that the emissions decrease in plants strong emitters of monoterpenes. grown at CO2 concentrations higher than ambient (Loreto et al., 2001; The emission potentials of many ornamental, alien species used Rosenstiel et al., 2003). This effect may be observed at CO2 concen- in urban landscaping and in gardens are missing (Owen et al., 2003; trations that are likely to be reached in the future (double or less than Noe et al., 2008b). Understanding the emissions of ornamental double the current concentrations) and should be therefore addressed species is also important in light of potential changes in vegetation in in future modelling efforts. urban landscapes driven by global change and the growth of urban There is now sufficient information to believe that the negative areas. Global warming and associated increases of evergreen emit- effect of CO2 on isoprene emission is ubiquitous and not species- ting exotic species in northern urban landscapes of northern hemi- specific. Arneth et al. (in press) included an empirical CO2-depen- sphere can importantly enhance the winter emissions (Niinemets dence into the Niinemets et al. (1999) model, and predicted that and Pen˜uelas, 2008). CO2 reduction of isoprene emission could partially compensate for In addition, stress- and time-dependent modifications of emission the emission increases with rising temperature. However, elevated potentials are only partly understood, but such adaptive responses can CO2 will enhance photosynthesis and growth of plants, in particular vastly affect ecosystem fluxes. Apart from gradual changes in BVOC vegetation leaf area, which may in turn increase the emission of emission capacity in response to day-to-day and seasonal differences isoprene by vegetation. The net effect of these interactions await in weather conditions (Guenther,1999; Sharkey et al.,1999), emissions experimental confirmation. triggered by biotic stresses such as herbivory or pathogen attack or Monoterpene emissions are also likely to be influenced by CO2, by abiotic stress factor such as elevated ozone concentrations but there is less experimental evidence than for isoprene (e.g. (e.g. Beauchamp et al., 2005), can potentially greatly influence whole Loreto et al., 2001). More studies are clearly needed to assess ecosystem fluxes. whether the different physico-chemical controls (see above) and the presence of small internal pools buffer the effect of CO2 and 6.4. BVOC fluxes over Europe, by compound and in relation make monoterpenes less sensitive to CO2 control. to the needs of photochemical oxidant models

6.2.5. Induced emissions 6.4.1. Flux measurement techniques In addition to the constitutive emissions, recent work demon- The development of disjunct eddy covariance (DEC) methods strates that synthesis of volatile isoprenoids is induced in many (Rinne et al., 2001; ) alongside the development of proton-transfer species in response to biotic (e.g. attack of herbivores and pathogens) reaction-mass spectrometry (PTR-MS, Lindinger et al., 1998)have and abiotic (e.g. ozone stress, heat stress) stresses (Beauchamp et al., enabled direct flux measurements of multiple VOC species simul- 2005; Blande et al., 2005; Loreto et al., 2006). taneously. The PTR-MS has also been used in a more traditional Previous work has shown that the emissions of volatile organic continuously sampling eddy covariance technique, in this mode the compounds are induced in response to stress in practically all plant flux of just one VOC species can be measured at a time (Karl et al., species, also in those not emitting volatile isoprenoids under optimal 2001b, 2001c). The DEC methods have been utilized in different growth conditions (e.g. tobacco and sunflower, Heiden et al., 1999; European ecosystems (Rinne et al., 2007; Davison et al., 2008). Beauchamp et al., 2005). In constitutively emitting species, the Inter-comparison experiments to validate these new techniques volatile isoprenoid blend differs between induced and constitutive have been conducted partly under ACCENT-BIAFLUX (Ammann emissions. For instance, European aspen (Populus tremula) emits et al., 2006; Neftel et al., 2007; Rinne et al., 2008). For isoprene isoprene as the main product in non-stressed conditions, but there also exists a fast isoprene sensor (FIS) based on chem- induced emissions are dominated by monoterpenes limonene and iluminescence enabling the application of eddy covariance a-pinene and sesquiterpenes (Blande et al., 2005). In non-stressed measurements (Guenther and Hills, 1998). conditions, the emissions of the monoterpene-emitting species High reactivity of several plant BVOCs imposes significant diffi- Pinus pinea are dominated by limonene, but the emissions in culties in determining whole canopy terpene emission fluxes by conditions of high temperature and low water availability are micrometeorological techniques. In particular, some monoterpenes dominated by linalool and ocimene; these emissions significantly and most sesquiterpenes have atmospheric lifetimes on the order of exceed the emission in non-stressed conditions (Staudt et al., 2000). minutes. High reactivity of these compounds can imply that before Current emission models do not consider ‘‘non-emitting’’ reaching the BVOC detector, a significant fraction of the emitted species, which, in addition to emissions from non-specific storage, compounds has already reacted in the atmosphere, resulting in may have significant induced emissions. Furthermore, modification underestimated emission fluxes (Rinne et al., 2007). To determine of gene expression profiles in response to stress and upon adap- the emissions of reactive terpenes, atmospheric chemistry models tation to stress may in many cases explain the modified emission have been inverted (Bonn et al., 2007). However, the lack of reactiion compositions. Accordingly, understanding induction mechanisms rate coefficients for many terpenes and the dependencies of these on and consideration of induced emissions is crucial in explaining and humidity and temperature seriously hamper the overall assessment predicting emission profiles. of the rates of emission and contribution to atmospheric reactivity.

6.3. Contemporary difficulties in scaling BVOC emissions 6.4.2. Isoprene from leaf to ecosystem Isoprene is the most studied biogenic VOC. European isoprene emissions have been studied at the ecosystem scale in a range of Parameterisation of models at ecosystem scales is bounded by landscapes. In some European ecosystems considerable isoprene a series of uncertainties. A key uncertainty is currently the lack of emission fluxes have been measured (Ciccioli et al., 1997; Davison reliable information of emission potentials (Arneth et al., in press). et al., 2008; Simon et al., 2005b). In contrast European boreal 5228 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 coniferous forests are generally very low emitters (Rinne et al.,1999). an orange orchard revealed substantial emission of b-caryophyllene, In measurements conducted above homogeneous conifer forest, the while the flux measurements conducted by REA method show the isoprene emissions from isoprene emitters concentrated in e.g. fluxes to be close to zero indicating rapid within and below canopy ditches, lakeshores and roadsides, will not be observed. Landscape chemical degradation (Ciccioli et al., 1999). scale emissions over southern Finland, estimated by a boundary layer budget method, show much smaller isoprene than mono- 6.4.5. Methanol terpene emissions (Spirig et al., 2004). In general, measuring forest The development of the DEC-PTR-MS has recently enabled sites, characterized by mixed composition, must account for the ecosystem scale flux measurements of methanol leading to plant species composition within the flux footprint. This has been considerable progress in our knowledge of ecosystem scale emission shown by Spirig et al. (2005), who observed the variation in of this compound. Methanol seems to be emitted from all ecosys- normalized ecosystem scale isoprene emission from a central tems and also from drying and decaying plant material. Methanol is European mixed broadleaf forest to be dependent on the abundance typically the second or third most abundantly emitted biogenic VOC of Quercus robur, which is a high isoprene emitter, within the flux after isoprene and monoterpenes in most ecosystems. footprint area. The measured ecosystem scale methanol emissions do not Flux measurements of isoprene often correlate well with leaf- generally fit the emission algorithms, used for monoterpene fluxes. A level measurements, reflecting the relatively long atmospheric recent empirical temperature dependent formulation has been pre- lifetime of isoprene (w1 h) compared with other shorter lived sented for methanol by Harley et al. (2007). From a mechanistic BVOCs. However, when the ecosystems are not homogenous, understanding of the physico-chemical control (see above), meth- correspondence between emissions at plant and ecosystem levels is anol emission should be regulated by stomata, in contrast to isoprene not straightforward. For example, the study conducted at Siikaneva and monoterpene emission. In field flux experiments, this kind of fen ecosystem using soil chambers (Helleńetal.,2006) and REA behaviour has not been generally observed. Brunner et al. (2007) technique (Haapanala et al., 2006) shows a considerable discrepancy have observed the methanol emissions from agricultural grassland between the isoprene emissions measured by these two techniques. ecosystem to be large in the morning relative to emissions in the The fluxes measured by Haapanala et al. (2006) under low CTCL evening. A similar observation was found in the recent ACCENT– values were substantially smaller than the model values, which may VOCBAS campaign on the Mediterranean macchia of Castelporziano. imply deeper penetration of PAR into the moss carpet at highlight conditions; a simple light penetration model slightly improved the 6.4.6. Acetone and acetaldehyde correlation (Haapanala et al., 2006). Acetoneandacetaldehydeintheatmospherearetheresultofboth primary emissions from biogenic and anthropogenic sources and 6.4.3. Monoterpenes secondary formation from other gaseous precursors. Fluxes of these European ecosystems are substantial sources of atmospheric carbonyls have been observed to be emitted from coniferous forests in monoterpenes and many flux measurement experiments have Europe (Rinne et al., 2007)aswellasintheUS(Schade and Goldstein, concentrated on these compounds. The diurnal variations of the 2001). Also the Mediterranean macchia ecosystem is observed to emit monoterpene fluxes above boreal coniferous forests appear to be these compounds (Davison et al., 2008). No emission of these relatively well reproduced by the temperature dependent Tingey– compounds from broadleaf deciduous forests has been reported. Guenther emission algorithm (Guenther et al., 1993). Monoterpene Anaerobic conditions in root system have been observed to enhance emissions from Mediterranean ecosystems are better described by the emission of acetaldehyde from plant foliage (Kreuzwieser et al., the light and temperature dependent isoprene emission algorithm 1999) as also mechanistically explained above. However, no ecosystem (Seufert et al., 1997; Schween et al., 1997), with important discrep- scale flux measurements of this compound, in conditions where the ancies likely reflecting non-specific storage and stress-dependent root systems was anaerobic, have been reported. changes in emissions (Niinemets et al., 2002a, 2002b, see above). At coniferous forest sites a diurnal concentration cycle with 6.4.7. Other compounds highest concentrations at night are typical (e.g. Hakola et al., 2000; The emissions of many compounds, other than isoprene, Steinbrecher et al., 2000; Rinne et al., 2000, 2005). This is due to the monoterpenes, methanol, acetone and acetaldehyde, have been too emission continuing during night-time, although at a lower rate small to be measured by micrometeorological flux measurement than during the day, and to considerably reduced turbulent mixing techniques. However, there are a few other compounds which at night. On the contrary, in the Mediterranean region, as well as in have been observed to be emitted by micrometeorological flux Amazonian tropics, and in European mixed broadleaf forest, where measurement techniques in certain ecosystems. Some western US the night-time monoterpene emission is practically zero due to the pine forests have been shown to emit 2-Methyl-3-buten-2-ol (MBO) light dependence of the monoterpene emission, daytime maxima in considerable amounts (e.g. Baker et al., 1999; Schade et al., 2000). are typical (Zimmerman et al., 1988; Schween et al., 1997; Rinne From European Pine species, no significant emissions of MBO have et al., 2002; Spirig et al., 2005). been observed (e.g. Hakola et al., 2006). It is noteworthy that drying The major monoterpenes emitted by forest ecosystems in Europe hay was observed to emit (Z)-3-hexenal and (Z)-3-hezenol and are a-andb-pinene and D3-carene. For example, monoterpene hexenyl acetates (Davidson et al., 2008a). These compounds appear emissionsfromNorwayspruceforestconsistofa-andb-pinene to be reliable markers of membrane damage and lipoxygenation, as (Christensen et al., 2000). However, in some Mediterranean ecosys- previously indicated (Loreto et al., 2006). tems limonene can form a significant part of the monoterpene emission (Schween et al., 1997) and, in the case of orange orchards, 6.5. The EU large field campaigns in the Mediterranean area: be the dominant monoterpene emitted (Christensen et al., 2000; from BEMA to ACCENT Darmais et al., 2000). Pioneering campaigns around the world (e.g. the SOS 1999 6.4.4. Sesquiterpenes campaign in North America, the LBA/CLAIRE 1999 campaign over the Due to the enhanced chemical reactivity of sesquiterpenes, atmo- Amazon, the SAFARI 2000 campaign in Southern Africa) highlighted spheric concentrations of these compounds are very small, making the predominance of isoprene as the most commonly emitted VOC by flux measurements extremely difficult. Enclosure measurements at vegetation, over different environments, and by different ecosystems, D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5229 spanning tropical to boreal forests. In Europe, however, a different presence of small sandy dunes, and by a gradient of soil humidity picture emerged. The BIPHOREP 1996–1997 campaign in boreal due to the presence of freshwater sources. Europe revealed the dominance of monoterpenes as the most abundantly emitted VOC from European boreal ecosystems. In otherwise 6.6. Remote sensing of BVOC clean northerly air masses, at least the growth, if not the formation, of organic aerosol, seems to be strongly influenced by the presence of Over the last decade space-based instrumentation, capable of biogenic VOCs. The most likely candidates contributing to this aerosol probing the lower troposphere, has reached the level of accuracy growth are monoterpene oxidation products (Lee et al., 2006). The necessary to quantify surface sources and sinks of trace gases from BEMA (Biogenic Emission in the Mediterranean Area) 1996 campaign observed variations in trace gas concentrations (Palmer, 2008). The highlighted the remarkable peculiarity of Mediterranean coastal only non-methane BVOC measured in the lower troposphere from vegetation that is almost uniquely characterized by monoterpene- space is formaldehyde (HCHO), a high yield product of VOC emitting species (Loreto et al., 1998). The reason for this distinctive oxidation that is measured from clear-sky backscattered solar trait of Mediterranean vegetation remains unknown. radiation at ultraviolet wavelengths (Chance et al., 2000). The main A new campaign during spring 2007 in the Mediterranean area, sinks of HCHO are oxidation by OH and photolysis leading to as part of the ACCENT and European Science Foundation programme a tropospheric lifetime of several hours. Fig. 5.3 shows the global VOCBAS programmes took place. The campaign was deliberately distribution of HCHO columns observed by the Ozone Monitoring held on the same site of the BEMA campaign, the large peri-urban Instrument during August 2006. natural preserved area of Castelporziano, in the conurbation of Oxidation of methane (CH4) by OH, the largest global source Roma. This site has two main characteristics that make it an excellent of HCHO, provides a uniform HCHO background of w100 pptv, case of study for biosphere–atmosphere interactions. First, the reflecting the w8-year lifetime of CH4. The limit of detection of 6000 ha wide preserved area of Castelporziano is a hot spot for HCHO from current space-borne instrument is approximately biodiversity in the Mediterranean, with more than 1000 plant 4 1015 molec cm2 (Chance et al., 2000), which is close to the species represented in the flora of the area (Davison et al., 2009). The source of HCHO from CH4 oxidation. Over the continental boundary main ecosystems going towards the sea are characterized by oak layer, oxidation of anthropogenic and biogenic VOCs provide an (Quercus ilex, Q. suber, Quercus cerris) and pine (P. pinea) forests, often additional source of HCHO that can reach on a local scale up to associated with a rich understory vegetation. The part of the Estate several ppbv, equating to columns over an order of magnitude facing the Tyrrhenian sea is characterized by sand dunes and determined by CH4 (Fig. 6.3). Observed variations in HCHO, deter- a humid retrodunal area, with a large and extremely well preserved mined by the oxidation of VOCs, therefore provide constraints on area covered by Mediterranean ‘‘macchia’’ vegetation, prevalently emissions of the parent VOCs. Horizontal transport smears the shrubs and small evergreen trees, such as Juniperus communis, Q. ilex, local relationship between VOC emissions and HCHO columns, Phillyrea latifolia, Arbutus unedo, Rosmarinus officinale, Erica arborea, the extent of which is determined by wind speed and the time- and Cistus incanus. Second, the preserved area is only distant 25 km dependent yield of HCHO from the VOC oxidation (Palmer et al., from the centre of Roma in the S-E direction. It is exposed to 2003). Over a number of global regions, variations in HCHO a constant wind circulation that favours transport of air masses from columns are determined by isoprene (Palmer et al., 2006), due to the city center during night-time, and from the sea during daytime. its rapid production and high molar yield of HCHO (Palmer et al., This periodically exposes vegetation to urban pollutants and may 2006). Other reactive biogenic VOCs, such as monoterpenes, also trigger formation of secondary pollutants that are contributed by have short atmospheric lifetimes but they quickly produce acetone BVOC precursors (Chameides et al., 1988; Di Carlo et al., 2004). with a high yield that has an atmospheric lifetime of weeks and The campaign (i) provided fluxes of BVOC from Mediterranean consequently slows down the production of HCHO (Palmer et al., vegetation, in a season during which plants are in optimal physio- 2006). Long-lived VOCs such as CH4 and CH3OH, while being the logical conditions prior to drought and heat stress conditions largest sources of HCHO, only contribute to the slowly varying experienced later in the year, but during which BVOC emisions are background of HCHO. thought to be constrained by leaf development limitations; Early work showed that the magnitude and distribution of (ii) investigated, by coupling concentration and flux measurements, GOME-derived isoprene emissions based on HCHO measurements the in situ extent of BVOC reactivity, and in particular whether in were more consistent with in situ measurements than either the situ BVOC oxidation could drive formation of secondary organic GEIA or BEIS2 isoprene inventories, based on Guenther et al. (1995) compounds in the atmosphere; (iii) identified whether BVOCs can (Palmer et al., 2003). Monthly mean distributions of HCHO, and act as precursors of photochemical smog; (iv) provided a second inferred isoprene emissions, during summertime are dominated by assessment, ten years after the campaign organized by the high values over the southeastern states of the USA (Chance et al., EC-BEMA project (Seufert et al., 1997), of BVOC emission in an 2000) due to a large density of isoprene-emitting oak trees over the area largely affected by anthropogenic and climatic changes, thus Ozarks Plateau (Wiedinmyer et al., 2005). Examination of GOME creating the foundation for a historical series of measurements orbital data revealed large variations in HCHO, explained by which may be especially important in view of current and future changes in surface temperature, which led to inferred monthly climate change factors, and, in particular, of the simultaneous and mean isoprene emissions that were significantly lower than those strong increase of temperature, drought and pollutants in the predicted by bottom–up models (Palmer et al., 2003). Later work Mediterranean area; and (v) fostered interdisciplinary collaboration showed that the observed seasonal and year-to-year variability was between the communities of biologists, atmospheric chemists and consistent with the MEGAN model (Guenther et al., 2006), but physicists, further catalyzing research on the important roles of GOME-derived isoprene emissions were 25% higher (lower) at the BVOCs in the environment. beginning (end) of the growing season (Abbot et al., 2003; Palmer The campaign was run in the macchia strip placed between the et al., 2006). Both MEGAN and GOME show a maximum over the dunes and the main forested land inside the Castelporziano Estate. Southeast US but disagree in the precise location, with implications The oak and pine forested area was extremely well characterized for modelling surface ozone (Fiore et al., 2005). during the BEMA campaign (1997) but the macchia vegetation Isoprene emissions from tropical ecosystems have been esti- received only limited attention (Owen et al.,1997). The macchia strip mated to contribute 75% of the global isoprene budget, but are not is characterized by a modest roughness of the terrain due to the well quantified. Over tropical South America, the widespread 5230 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

Fig. 6.3. Formaldehyde columns (1016 molec cm2) retrieved from the NASA Aura Ozone Monitoring Instrument (OMI) for August 2006, courtesy of Thomas Kurosu, Harvard Smithsonian Center for Astrophysics. extent of biomass burning in the dry season means that without consequently lead a greater number of useful data points; 2) spatial high-resolution data the only practical approach is to use data disaggregation of different HCHO sources, e.g. biomass burning and over west Amazonia, which is largely unaffected by fires (Barkley biogenic VOC emissions over tropical regions, which can lead a better et al., 2009). There is a strong seasonal cycle of GOME HCHO description of land-surface processes; and 3) their usefulness in columns over this region reproduced each year during 1996–2001, planning and executing measurement campaigns. For example, characterized by large values in the wet and dry seasons, sepa- analysis of GOME-2 and OMI HCHO data, which have local overpass rated by low values in the wet-to-dry transition period (May– times of 09:30 and 13:30, will allow us to develop a crude under- July); this is consistent with in situ isoprene concentration standing of the diurnal cycle of BVOC emissions on continental scales. measurements (Palmer et al., 2007). This large-scale reduction in Knowledge of the complex organic chemistry associated isoprene emissions suggests a major temporary shift in underlying with BVOC oxidation will only improve with a concerted effort to meteorology or phenology, but its origin remains unclear. This increase the number of laboratory and field measurements. With study found that MEGAN and GOME were in better agreement in the rapid increase in available remotely sensed datasets that could the dry season, when GOME isoprene emissions could not be be brought to bear on estimating BVOC emissions (e.g. HCHO, leaf explained by changes in surface temperature. GOME isoprene phenology, land cover) there should be scope to develop new emissions in the wet season could be not explained by changes in functional descriptions of isoprene emission that are independent surface temperature, precipitation or soil moisture, suggesting of the assumptions made in traditional bottom–up models derived either an unexplained process that determines isoprene during from in situ measurements. this season or noisy data (Barkley et al., 2009). These substantial open questions will be readdressed with data from newer sensors 7. Deposition and resuspension of aerosols onto and should be the subject of extensive year-long ground-based and from terrestrial surfaces measurement campaigns. There are a number of uncertainties associated with the HCHO 7.1. Introduction measurement and the approach used to infer surface emissions of isoprene from these measurements (Palmer et al., 2003; Millet et al., Aerosols present a complex multi-variate and multi-scale 2006), which lead to uncertainties that total more than 100% of problem to environmental research. They have strong impacts on estimated emissions (Palmer et al., 2006). Work related to the anal- climate indeed they represent the largest uncertainties in our ability ysis of GOME data has suggested that HCHO production predicted by to predict climate change (IPCC, 2007), human health and provide chemical mechanisms typically used by large-scale chemistry- a means for pollutant deposition to sensitive ecosystems (trans- transport models are in error by more than 25% (Palmer et al., 2006). porting e.g. nitrogen, sulphur and toxic metals). A vital component of Current studies that determine VOC emissions using HCHO the global aerosol cycle is deposition of many critical secondary column data are already focusing on data from newer space-borne process-derived condensed phase compounds as well as primary sensors (e.g. Aura OMI and MetOp GOME-2) that have better spatial generated aerosols, both in the ultrafine and coarse modes. The (100 s km2) and daily temporal resolution, enabling more detailed majority arise from the consequences of anthropogenic activities testing of current bottom–up inventories. The advances in resolution, associated with global industrialisation and urbanization where in particular, improve: 1) the probability of cloud-free scenes and large emissions of reactive nitrogen species lead to an increase in D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5231 nitrogen aerosol formation which is eventually removed by wet or covariance (EC) measurements of size-resolved aerosol number dry deposition. Sulphate aerosol remains an important issue in fluxes (e.g. Duan et al., 1988; Gallagher et al., 1997; Nemitz et al., the Eastern US and China. Over the last 150 years the atmospheric 2002a; Sievering, 1983; Vong et al., 2004). The measurements particulate loading has changed from coal and other solid fuel usually cover the size spectrum between 0.1 and 0.5 mm, but even in burning to modern combustion processes that liberate a greater this size range the particle statistics of these instruments have often preponderance of submicron, ultrafine particles. This has initiated been marginal in deriving statistically significant fluxes. Several a paradigm shift in some quarters of the relative importance of studies have attempted to extend measurements to smaller and also coarse mode as opposed to fine mode particulates and their to larger sizes. Particles significantly <0.06 mm cannot be sized with behaviour for mainly health related reasons. This shift will likely current optical techniques. Instead, recent studies have attempted to move into a third phase where emissions from nano-particle measure size-segregated fluxes of smaller particles, either using the technologies are starting to play an increasing role. In addition, it is relaxed eddy accumulation (REA) technique combined with size becoming obvious that particulate matter provides an area of policy selection using a differential mobility analyser or interpreting total conflict: efforts to curb PM concentrations to protect human health particle number fluxes during periods where a certain size-range are likely to reduce global dimming and thus further accelerate dominated the flux (Gro¨nholm et al., 2007; Pryor, 2006). Due to climate change, although there are also components, such as soot, limited counting statistics, fluxes had to be averaged over many days that have a negative impact on both human health and the climate to obtain robust statistics and these measurement methods are system. The primary aims of research into the biosphere/atmosphere therefore not yet suitable to study short-term processes (Fig. 7.1). exchange of particles are: Variability between measurements is likely to be linked to differences in turbulence, canopy morphology (including leaf area index) (a) to improve our estimates of primary aerosol emissions from and surface roughness length (cf. Section 7.4.1). diffuse sources and their parametrisations, Size-segregated EC fluxes of larger particles are only possible (b) to measure directly the contribution of particle deposition to when these particles are abundant and occur as the result of specific the deposition of compounds that are detrimental to ecosys- mechanisms, e.g. in dust storms, biomass burning or industrial tems or may accumulate in water, soils or crops (e.g. N and S processes. High volume, closed path aerodynamic Mie scattering compounds, heavy metals and nano particles), time of flight optical particle counters, for sizes 0.5 < Dp < 20 mm, (c) to derive parametrisations of the deposition velocity (Vd)of and open path forward scattering optical particle counters have been particles, for inclusion into CTMs e.g. aimed at predicting used to measure deposition rates of super-micron particles and fog deposition, human health impacts and climate impacts, droplets (e.g. Beswick et al., 1991; Burkhard et al., 2002; Klemm and (d) to study aerosol formation and dynamics in the atmosphere. Wrzesinski, 2007; Kowalski and Vong, 1999). As a result of current instrument limitations, measurement evidence is sparse on depo- If the models predict the size distribution of the aerosol explic- sition rates in the important accumulation mode (0.3–2 mm), itly, Vd needs to be parametrised as a function of particle diameter which contains much of the mass of sulphur, nitrogen and secondary (Dp). By contrast, where the models only deal with the bulk species, organics. Recently developed mass-based flux measurement Vd may be derived from measurements of the individual compounds approaches based on time-of-flight aerosol mass spectrometry (see (e.g. Ruijgrok et al., 1997) or, more commonly, from a weighting of below) may go some way towards filling this gap in the future. Vd(Dp) with a typical size distribution of the aerosol component. It is sometimes easier to measure super-micron emission fluxes. For example, Fratini et al. (2007) reported measurements of desert 7.2. Review of new measurement approaches and instrumentation dust resuspension, and Nemitz et al. (2000c) presented urban EC flux measurements in the range 0.8–10 mm, made with Progress in the quantification and parameterisation of surface/ atmosphere exchange of particles and aerosol compounds is closely related to developments in the measurement technology. In the 3 Beech forest (mean) 1970s and 80s measurements of aerosol dry deposition were made dep. only, CPC (Pryor, 2006) Beech forest (median), dep. only, in the wind tunnel or using surrogate surface collectors, such as 2 CPC (Pryor, 2006) knife-edge collectors, inverted frisbee type dust deposition gauges Scots pine, CPC nucleation event and moss bags. Although these techniques are still being used, they (Gaman et al., 2004) have attracted serious criticism as their aerodynamic properties are Scots pine, DMA REA 10 (Gronholm et al., 2007) usually not representative for the surface for which deposition is to 9 be estimated. The lack of an understanding of the relationship 8 between deposition on these collectors and deposition to the 7 6 surrounding landscape reduce the value of the measurement to 5 [mm/s]

trend detection. More recently, non-intrusive micrometeorological d

V 4 flux measurement techniques have increasingly been extended to measure surface/atmosphere exchange particle fluxes at the 3 field scale. Measurements of particle fluxes fall into two categories: particle number fluxes (total or size-segregated) and chemically 2 resolved aerosol fluxes.

7.2.1. Flux measurements of particle numbers (size-resolved or total), without information on chemical composition 1 789 23456789 2 These measurements are usually used to derive (size-dependent) 10 100 deposition velocities which can be used in atmospheric transport D p [nm] and deposition models. Since the 1980s, fast optical particle counters (e.g. OPCs such as ASASP-X/555X, Particle Measurement Systems; Fig. 7.1. Summary of measured size-segregated particle deposition velocities to forest FAST, Droplet Measurement Technologies) have been used for eddy for particles with diameters < 100 nm. 5232 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 aerodynamic particle sizers (APS 3320, TSI Instruments), both made and organic aerosol to urban areas and forests (Nemitz et al., 2008; in conditions where fluxes were large. Phillips et al., in preparation; Thomas, 2007; Thomas et al., 2009, In general, better counting statistics can be achieved when 2007). The Q-AMS monitors only one single mass/charge ratio (m/z) integrated particle number fluxes are measured over larger size at a time. However, the quadrupole MS can be switched very rapidly ranges. For example, condensation particle counters (CPCs) are now so that quasi-continuous time series of concentrations can be more commonly used to measure total particle number fluxes with established at typically 10 different m/z at 10 Hz, similar to the use of a lower cut-off between 2.5 and 20 nm over ice, seawater, short and the PTRMS for VOC measurements. Since >100 different m/z tall vegetation canopies, as well as urban areas (e.g. Buzorius et al., contribute to the organic mass spectrum, with the Q-AMS, the total 1998; Buzorius et al., 2001; Dorsey et al., 2002; Held et al., 2006; organic aerosol mass flux has to be estimated from fast response Martensson et al., 2002; Nemitz et al., 2002a; Nilsson and Rannik, measurements at a few m/z. The arrival of the next generation AMS 2001). CPC derived flux measurements are dominated by particles based on a high-resolution time-of-flight mass spectrometers in the range 10–100 nm, with smaller particles dominating during (HR-ToF-AMS) (De Carlo et al., 2006) provides the prospect of nucleation events (Buzorius et al., 2001). Depending of the model monitoring all m/z continuously at 10 Hz. This should enable a fully used, CPCs have a response time of around 1 s, which is sufficient to quantitative flux measurement of the organic fraction and provide measure fluxes from taller towers, but requires flux corrections for data to apply statistical approaches, currently used to deconvolve the shorter vegetation. An alternative EC flux measurement approach organic mass concentration in different organic aerosol classes (e.g. that integrates overall particles was implemented by Fontan et al. Ulbrich et al., 2009), to the flux measurement. (1997) based on particle counting through a combination of corona charging and detection by electrometers. Only very few gradient measurements of small particle number fluxes have been reported 7.3. Area sources of particles in the literature (Hummelshoj, 1994) due to the large errors associated with these measurements. Work has started to extend 7.3.1. Resuspension EC approaches to the measurement of particle fluxes from moving Resuspension of particles has been studied extensively, both theo- platforms such as aircraft (e.g. Buzorius et al., 2006) and ships retically, in the wind tunnel or through concentration measurements (Norris et al., 2007). (Braaten and Paw, 1992; Harrison et al., 2001; Nicholson, 1988, 1993; Nicholson et al.,1989). A full review of the understanding of this process 7.2.2. Flux measurements of individual aerosol chemical species is beyond the scope of this paper. Instead, we here focus on a recent Measurements of chemically resolved aerosol fluxes can be used development involving the first application of micrometeorological to quantify deposition inputs directly, to investigate effects of flux measurement techniques to the direct measurement of resus- aerosol composition on exchange rates and to understand apparent pension fluxes, and their potential to derive new parametrisations of emission fluxes. The number of studies that have applied micro- the process. Nemitz et al. (2000f) measured super-micron size-segre- meteorological approaches to measure fluxes of aerosol compounds gated aerosol fluxes measured with an Aerodynamic Particle Sizer (APS has been surprisingly limited. Up to the 1990s, the main option 3320, TSI Inc.) from a tower, some 65 m above the city of Edinburgh, was gradient measurement with labour intensive manual sampling Scotland. The measurements, binned according to diameter and wind techniques based on filter packs or denuder/filter combinations speed lead to a parameterisation of the form: (Duyzer, 1994; Rattray and Sievering, 2001; Wyers and Duyzer, bðDpÞ 1997), where a key challenge is to achieve the precision required to dFm Dp dlog Dp ¼ am Dp U resolve the very small aerosol gradients, which are often <3%. am Dp ¼ exp 68 :69þ73:39 1exp 0:730Dp½mm Manual sampling techniques have also been used in REA approaches b Dp ¼ 20:12exp 0:506Dp½mm ð1Þ to measure fluxes, e.g. of sulphate to a maize crop (Meyers et al., 2006) and of ions and heavy metal above a city (Nemitz et al., where U is wind speed measured at a height of 65 m. 2000d). A family of automated real-time gradient monitors, based The measurements show that above U (65 m) ¼ 6ms1 resus- on gas and aerosol capture by continuously flushed wet rotating pension becomes an important particle source in the urban envi- denuders and steam jet aerosol collectors, respectively, and online ronment, with a mode centred around a Dp of 2.8 mm, which analysis by ion chromatography and/or flow injection analysis increases with decreasing wind speed. An attempt to include traffic þ (for NH4 )(Thomas et al., 2009) has been used in a number of studies activity in the parametrisation failed due to the overriding effect of to measure deposition of water-soluble inorganic aerosol compo- wind speed. This suggests that, although vehicle induced resus- nents (Nemitz et al., 2004b, 2000e). pension may be important to lift particles off the surface at street Eddy covariance measurements of aerosol chemical species were level, high wind speeds are nevertheless required to flush these out 2 first presented for SO4 deposition to grassland, based on an analyser of the street canyons. It should be noted that the windy periods with with thermal conversion to SO2 (Wesely et al., 1985), with no further largest coarse particle emissions did not result in the largest studies until the advent of aerosol mass spectrometry offered the concentrations, due to increased dispersion during these periods. prospect for fast measurement of a number of aerosol compounds. Similarly, Fratini et al. (2007) measured coarse aerosol fluxes Held et al. (2003) theoretically investigated the suitability of aerosol during desert storms in the Alashan desert in Nothern China, using mass spectrometers based on single-particle analysis by laser abla- an optical particle counter. The authors found that the dependence 2 1 tion and ionisation for disjunct eddy covariance flux measurements, of the resuspension flux (in mgcm s )ofPM1,PM2.5 and PM10 on 1 dealing with the limited counting statistics and quantification issues u* (in m s ) could be described by the power relationships of 3.11 3.34 3.36 related to this instrument (De Carlo et al., 2006). An alternative F1 ¼ 469u* , F2.5 ¼ 6220u* and F10 ¼ 47,500u* , respectively. It instrument, the Aerodyne Aerosol Mass Spectrometer (AMS), should be noted that these two studies address different resus- which is based on thermal vapourisation coupled with electron pension processes, reflecting road dust resuspension with vehicle impact ionisation, averages over a much larger aerosol population contribution, and natural saltation processes, respectively. and is quantitative for submicron aerosol components that are non- refractory, i.e. volatilise at the vapouriser temperature of w600 C. An 7.3.2. Urban emissions of aerosols operational EC system using the quadrupole-based AMS (Q-AMS) In recent years, flux measurement techniques have been 2 (Nemitz et al., 2008) has been used to measure fluxes of NO3 ,SO4 extended to the urban environment to quantify emission fluxes of D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5233 trace gases such as CO2,N2O, CO and VOCs (Nemitz et al., 2002b; cities (Boulder, US; Mexico City; Gothenburg, Sweden; Manchester, Velasco et al., 2005; Vesala et al., 2007), but also of particles. Total Edinburgh and London, UK) (Grivicke et al., 2007; Nemitz et al., number fluxes have been measured with condensation particle 2008; Phillips et al., 2007; Thomas, 2007). The AMS measures counters over several cities (Dorsey et al., 2002; Martensson et al., total organic aerosol mass contained in particles with 60–800 nm 2006; Nemitz et al., 2000f). Martin et al. (in press) recently compared vacuum-aerodynamic diameter and volatilizes at typically 600 C. the pattern of particle number fluxes measured at four different More information on the organic aerosol classes can be obtained locations, three of which are shown in Fig. 7.2. Fluxes, typically from the organic mass spectrum, with statistical techniques covering the diameter range 0.01 (or 0.003) to 2 mm, ranged from (e.g. Ulbrich et al., 2009), which can be used to separate the organic 5000 to 70,000 # cm2 s1 and showed a clear dependence on traffic mass flux into fluxes of (primary) hydrocarbon-like organic aerosol activity confirming the role of traffic emissions as the major source (HOA) and (secondary) oxygenated organic aerosol (OOA), where of particles in the urban area. They derived a parametrisation for the OOA can often be divided into a more (OOA-I) and a less (OOA- 2 1 the flux (FPred in cm s ) over each city based on friction velocity II) oxidized component. The measurements to date show clear 1 2 (u* in m s ), sensible heat flux (H in W m ) and traffic activity (TA diurnal fluxes of HOA reflecting the pattern of the surface sources 1 in veh s ) of the form (Fig. 7.3). However, the flux ratios of HOA/CO and HOA/CO2 vary h i over the day, indicating that either (a) some of the HOA evaporates

FPred ¼ C EFfriction u* þEFheat H þEFtraffic TAF0; (2) at rates that vary over the day (e.g. Robinson et al., 2007) or (b) that the fuel mix contributing to the emissions of HOA and CO varies which is shown in Fig. 6.3 for comparison. Here C is a site-specific over the night. Measurements suggest that food cooking may factor in the range 0.12–0.55. The emission factors are contribute to HOA emissions in the evening in London. Fluxes of 3 6 1 1 EFfriction ¼ 4500 cm ,EFheat ¼ 6.53 10 W s and EFtraffic lies in OOA-I appear to be mainly downwards consistent with its the range 9000–12,600 veh1 cm2, depending on the location of production during long-term transport, while small upward fluxes the traffic census site. The sink flux (F0) ranged from 13,000 to of OOA-II were measured, indicating that some OOA-II formation 57,000 cm2 s1. occurs below the measurement height of typically 30–200 m. The 2 In the Edinburgh study of Nemitz et al. (2000f) aerosol number urban flux measurements indicate that SO4 is deposited to most fluxes were dominated by traffic activity, while the aerosol mass city centres. Apparently, with the introduction of ultra low sulphur emission fluxes were dominated by the wind-driven resuspension fuels, there are no primary sources of this compound. Fluxes of NO3 described in the previous section This may be different for less windy were more variable: in Gothenburg, Edinburgh, London and locationsasdemonstratedbySchmidt and Klemm (2008),who Boulder, net emission was observed, but fluxes were dominated by presented flux measurements of super-micron particles made with individual, often cool or foggy days, indicating urban NO3 forma- a novel disjunct eddy covariance system, based on an Electronic Low tion under these conditions. By contrast, above Manchester and Pressure Impactor (ELPI, Dakati, Finland), indicating net coarse-mode Mexico City, the average flux was downwards. deposition to the German town of Mu¨ nster. During the measurement periods, wind speed averaged 8.0 m s1 in Edinburgh and 4.4 m s1 in 7.4. Dry deposition of particles Mu¨ nster (Klemm O., personal communication). Donateo et al. (2006) reported flux measurements of PM2.5 above an urban area made with 7.4.1. Dry deposition rates to vegetation an optical detector calibrated against gravimetric PM2.5 measure- Dry deposition of atmospheric particles can account for a large ments. These measurements indicated continuous net upward fluxes fraction, sometimes more than half, of the total deposition of many and represent a combination of Aitken, accumulation mode particles important chemical compounds in the atmosphere, (e.g. nitrate; and super-micron particles. Lovett, 1994), contributing significantly to global biogeochemical Chemically resolved flux measurements using the AMS EC cycling. Understanding atmospheric deposition processes in relation technique described above have now been made over a range of to the ever increasing sources of fine particles in particular is therefore becoming a research priority. In general, both aerosol mass and number, and, increasingly, surface area, must be determined to assess the environmental impacts of anthropogenic activities. Mapping between number and mass fluxes however requires either a detailed knowledge of the aerosol mass size distribution at relatively high temporal resolution or by direct measurement of the aerosol deposition flux as a function of both size and chemical composition. In this short summary we will critique the present level of understanding from an observational perspective and identify the current gaps in our knowledge. There have been a number of recent reviews on the subject of atmospheric aerosol deposition which have attempted to collate the sparse experimental results available from the previous two and half decades. These consist of many disparate and difficult to compare or even reconcile, methodologies. The reviews, whilst achieving this difficult process in some respects, have succeeded mainly in highlighting the general lack of a systematic approach towards improved understanding of mechanistic deposition processes and, despite best efforts, have simply reinforced the view of continued large uncertainties. Reviews have been very much focused on either a modelling (Petroff et al., 2007b; Zhang and Vet, 2006) or a measurement perspective (Petroff et al., 2007a; Pryor et al., 2007). Fig. 7.2. Summary of diurnal patterns of measured particle number fluxes (dotted lines) and their parametrisation (solid lines) for three UK cities: M – Manchester; L – London; Many regional pollutant deposition models are currently E – Edinburgh; Win06 – winter 2006 etc. struggling to correctly incorporate physico-chemical properties of 5234 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

400 40 Manchester 300 Manchester 20 200 0 100 -20 0 -40 -100 200

London HOA flux [ng m London ] 150 1200 ] -1 -1 NO s

s 100

-2 800 -2

50 3 - 400 flux [ng m 0 200 0 -50

-2 Boulder Boulder flux [ng m 40 - s 3 -2 100 -1 s ] HOA flux [ng m NO

20 -1 0 ] 0 -100 120 40 Gothenburg Gothenburg 80 20 40 0 0 -20 0 6 12 18 24 0 6 12 18 24

Fig. 7.3. Averaged diurnal cycles of the ﬂuxes of hydrocarbon-like organic aerosol (HOA) and nitrate (NO3 ) over a range of cities as measured by eddy covariance using an Aerodyne Aerosol Mass Spectrometer (data from Nemitz et al., 2008a (Boulder); Phillips et al., 2007 (Manchester, London) and Thomas, 2007 (Gothenburg)). The grey range indicates the 5th–95th percentile.

aerosols using realistic coupled sectional approaches, particularly (cf. e.g. Pryor et al., 2008b). The data must be treated with with respect to secondary organic aerosols. However, it could be circumspection as (a) little account of particle composition is stated that the scientific community has not delivered any signifi- provided in many of the studies reporting these data, (b) the sizes cant improvement in the accuracy of model predictive capabilities reported are an ad hoc mixture of optical, electrical mobility, mass for the atmospheric aerosol deposition pathway over the last two and aerodynamic diameters with little quantitative information on decades, compare for example one of the first reviews of model the influence individual measurement techniques may have in uncertainty, Ruijgrok et al. (1997), with e.g. Petroff et al. (2007b). altering actual depositing particle size (which will be particle The aerosol modelling and composition community are pushing growth factor and hence composition dependent) and (c) system- ahead with such developments whilst seemingly unaware of the atic detailed information on the morphology of the surfaces is not poor state of knowledge of deposition processes and caution is always reported which hinders model development. required to avoid simply wasting research effort here. Whether the current level of understanding and uncertainty is acceptable 7.4.1.1. Friction velocity (u*). Increased turbulence increases trans- depends on the compound of interest and its position with the port in the turbulent part of the atmosphere, decreases the effective aerosol mass size distribution prevalent in the atmosphere. Little thickness of the quasi-laminar sub-layer and increases the drag in the way of detailed sensitivity studies has been available since coefficient. It is therefore not surprising that Vd increases with Ruijgrok et al. (1997). Feedback of such sensitivity studies to the increasing u*. Most modelling approaches and measurements indi- measurement community would also appear to be an area that cate a near-proportion relationship between Vd and u* for submicron requires improvement (Zhang and Vet, 2006). particles (Fig. 7.4). There has also been little in the way of any new laboratory investigation, at least for atmospherically relevant conditions, that 7.4.1.2. Surface roughness length (z0) and canopy morphology. The can usefully inform these communities on specific gaps in knowl- effect of the surface roughness length (for closed canopies: edge that need to be pursued. While some progress is being made z0 w 0.1 canopy height) extends beyond its effects on increasing to highlight gaps in knowledge with respect to models (Petroff u*. Vd for forest tends to be by a factor of 5–10 larger than Vd for et al., 2007b), these again show that different model descriptions of grass, due to the increased height of the canopy and leaf area index atmospheric particle deposition, which rely on very limited semi- and the enhanced turbulence induced by forest canopies. Davidson empirical data and highly tunable, collection efficiency parame- et al. (1982) showed theoretically that even for the same vegetation terisations, are as variable or more so than the atmospheric type (grassland), Vd may change within a factor of 5, depending on observations that do exist (e.g. Zhang and Vet, 2006). Some the exact morphology of the vegetation. Similar results were more improvements in relating natural surface morphology descriptions recently obtained by Petroff et al. (2007b) for forests, emphasizing to wind tunnel studies have been made. the influence of leaf dimensions and orientation on Vd. There is In the following we explore the dependence of particle depo- measurement based evidence as well: Ould-Dada (2002) used wind sition velocity (Vd) on key parameters, in comparison with tunnel studies to investigate the dry deposition velocity of submi- measurements. Most of these measurements were made over cron particles to model Norway spruce (Picea abies). A total canopy forests, where they are generally easier to obtain than over short deposition velocity of 5 mm s1 was found which is in line with vegetated surfaces for many reasons related to the micrometeoro- previous micrometeorological measurements to real forest cano- logical flux technique. The fluxes have been determined using pies reported in the literature. However, the deposition pattern was mainly but not exclusively direct micrometeorological techniques found to be a highly complex function of height within the canopy. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5235

tall vegetation: 10 forest (0.10-0.18 μ m) (Gallagher et al., 1995) forest (0.18-0.24 μ m) (Gallagher et al., 1995) forest (0.24-0.30 μ m) (Gallagher et al., 1995) forest (0.30-0.50 μ m) (Gallagher et al., 1995) forest (0.05 μ m) (Gaman et al., 2004) forest (0.05-0.75 μ m) (Lamaud et al., 1994) 1 forest (0.05-0.06 μ m) (Pryor et al., 2009) forest (fog) (Vermeulen et al., 1997) forest (sulphate) (Wesely et al., 1983) ] forest (< 0.02 μ m) (Buzorius et al., 2001) -1

0.1 short vegetation:

[cm s [cm grass (< 2 μ m) (Allen et al., 1991) d

V grass (fog) (Dollard & Unsworth, 1983) grass (sulphate) (Neumann & den Hartog, 1985) grass (sulphate) (Nicholson & Davies, 1987) grass (sulphate) (Wesely et al., 1985) μ 0.01 field/snow (0.15-0.30 m) (Duan et al., 1988) field/snow (0.50-1.0 μ m) (Duan et al., 1988) moorland (0.12-0.13 μ m) (Nemitz et al., 2002) moorland (0.15-0.16 μ m) (Nemitz et al., 2002) moorland (0.22-0.24 μ m) (Nemitz et al., 2002) moorland (0.4-0.5 μ m) (Nemitz et al., 2002) 0.001 heathland (0.4-0.5 μ m) (Nemitz et al., 2004)

0.0 0.2 0.4 0.6 0.8 1.0 u -1 * [m s ]

Fig. 7.4. Dependence of small particle deposition on friction velocity (u*) for a range of surfaces. Adapted from Pryor et al (2008b). Measurements over aerodynamically rough vegetation are shown with bold lines and symbols, while thin lines and symbols are used for measurements over short vegetation. The greyscale of lines and symbols refers to the measured or estimated particle size (darker shading referring to larger sizes).

More studies such as these are needed to improve model devel- Interception and impaction are most effective in the intermediate opment and in-canopy gradient measurements are needed to size range, but less effective than the other two processes. The validate multi-layer deposition models. resulting trough in Vd(Dp)(Fig. 7.5) is partially responsible for the survival of the accumulation mode in the atmosphere. 7.4.1.3. Particle diameter (Dp). Both theoretical approaches and When comparing measurements of Vd(Dp) with each other or measurements show an effect of particle size on Vd: the main with model results it needs to be borne in mind that different deposition processes (Brownian diffusion, interception, impaction instruments measure different types of diameter (i.e. geometric, and gravitational settling) are all size-dependent. Brownian diffu- aerodynamic, vacuum-aerodynamic, electro-mobility and optical), sion is responsible for high Vd for small particles (Dp < 100 nm), which are often difﬁcult to compare without exact information while gravitational settling is the dominant process for Dp > 5 mm. on particle shape and composition. Some instruments dry the

Fig. 7.5. Evolution of the deposition velocity Vd with the particle diameter Dp on grass and grass-like canopies (lhs) and coniferous canopies (rhs) for friction velocity between 0.35 and 1 0.56 m s , as given by various measurement campaigns and six existing models from the literature. Canopy characteristics used by models are hc ¼ 0.07 m, z0 ¼ 0.01 m, LAI ¼ 4, dn ¼ 3 mm, a ¼ 1.78 for grass and h ¼ 17 m, hc ¼ 7m,z0 ¼ 1 m, LAI ¼ 22, dn ¼ 1 mm, a ¼ 3.81 for forest. Deposition velocities are recalculated at the same reference height zR ¼¼100z0. The parameters of Slinn’s model (1982) are fIN ¼ 0.01, dr ¼ 20 mm, cv/cd ¼ 1/3, b ¼ 2. The model of Zhang et al. (2001) is applied on Land Use Categories #6 (grass) and #1 (evergreen- needle-leaf trees), the corresponding parameters being, respectively, fIM ¼ 1.2 and 1, and fB ¼ 0.52 and 0.56; from Petroff et al. (2007b). 5236 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 particles, while others measure the wet size. The wet size at the reported with measurements (in particular on canopy structure). The measurement height may not reflect the size at which they impact high sensitivity of the models to the canopy structure further adds with the surface, due to water uptake or release during the depo- uncertainty to the application of simple generalized parametrisations sition process, in a response to humidity gradients. Despite recent at the regional scale, where input parameters are limited. advances in measurement technology, it is still not known how particle composition, particle shape and particle hygroscopicity 7.4.3. Dry deposition rates to urban areas influence micro-scale deposition mechanisms and collection Very little is currently known about deposition rates to urban efficiencies onto and by different surface types with very different areas, despite their importance for estimating the contribution of microstructures, which are known to significantly influence e.g. aerosol deposition to the soiling and weathering of buildings, and aqueous phase aerosol contact angle and therefore the likely for the atmospheric lifetime in the atmosphere (Pesava et al., 1999). collection efficiency. Although aerosol deposition measurements have been made in cities, these were usually made with surrogate collectors (e.g. Yun 7.4.1.4. Atmospheric stability (z ¼ 1/L). There is strong evidence et al., 2002), which are unlikely to be representative of the uptake from a range of studies that Vd can be greatly enhanced in by urban structures. Alternatively, the soiling of building has been unstable conditions. Fig. 7.6 summarizes the findings from several studied, which provides information of the aerosol deposition to field studies, by exploring the dependence of Vd, normalized by a particular receptor, but not on the net removal rate from the u*, on the inverse of the Monin–Obukhov length (L), a standard atmosphere to the urban matrix (Horvath et al., 1996). measure of atmospheric stability. The cause for this enhancement Application of micrometeorological flux measurement techniques is not fully understood and therefore difficult to reproduce in to the urban environment has now been demonstrated (see Section numerical models. 7.2.2 above). However, the net flux of particles above urban areas is dominated by emission sources from the city and deposition rates 7.4.2. Parameterising and modelling deposition rates can only be applied if a chemical aerosol species or size-class is found The first detailed sensitivity study of aerosol deposition models which is not emitted from the city. Nemitz et al. (2000d) presented compared to field observations was conducted by Ruijgrok et al. initial measurements of chemically resolved aerosol fluxes at (1997). They reported a factor of 5 uncertainty in model predictions a coastal site and showed that chloride was deposited at low wind for submicron aerosol deposition velocities based on input uncer- speeds, presumably reflecting deposition of sea salt, while it was tainty. Despite this there was general consensus that dry deposition emitted during windy periods, probably reflecting wind-driven measurements (mainly by gradient filter pack and throughfall tech- resuspension of previously deposited material. Similarly, Nemitz 2- niques) yielded deposition rates significantly larger than analytical et al. (2008) measured SO4 deposition fluxes to urban environment models were predicting for forested surfaces compared to grasslands with the Q-AMS EC system. These measurements suggest deposition (Erisman, 1993), which led to some improvement in aerosol collec- velocities in the range of 2–6 mm s1, but will need to be supported tion efficiency descriptions in models. Later the first eddy covariance with data from other cities. As mentioned above, Schmidt and Klemm measurements at the same locations tended to confirm this, (2008) detected net deposition of PM2.5 to a German town, but these notwithstanding the sampling issues associated with aerosol growth fluxes almost certainly contain an upward component. factors mentioned below (Erisman et al., 1996). The latest review (Petroff et al., 2007b) suggests this uncertainty has now been 7.5. Uncertainties reduced, to around a factor of 3. Efforts to reduce this uncertainty further are restricted by the quality of the measurements (as dis- 7.5.1. Uncertainties in the application of micrometeorological flux cussed in Section 6.4 below) and the completeness in the metadata measurement techniques for deriving the local flux Technical challenges in applying micrometeorological techniques to the measurement of aerosol fluxes go beyond those encountered 0.04 for gas flux measurements. Aerosol fluxes are often small and grass; Wesely et al. (1985) deposition rates slow, resulting in small concentration differences forest; Gallagher et al. (1995) heathland; Nemitz et al. (2004) that need to be resolved for gradient and REA measurements. Simi- D μ p = 0.1 m larly, the relative corrections, e.g. for density fluctuations (Webb et al., 0.03 0.2 μm 1980), may become large and can easily result in reversal of the sign μ 0.3 m of the flux. A continuing challenge of particle flux measurements is 0.4 μm 0.5 μm that, due to the limited counting statistics of the measurement, *

u standard data processing techniques, such as tests and corrections

/ 0.02 based on co-spectral analysis, and non-stationarity tests are difﬁcult d

V to implement. While most gas analysers respond to many thousands of molecules per tenth of a second, aerosol counters may only detect tens of particles resulting in statistical uncertainties (Fairall, 1984). 0.01 Similarly, in mass-based measurements the contribution from a few large particles may greatly affect gradients and EC results. Different aerosol measurement instruments respond to different parameters, not all of which are conserved. For example, artificial fluxes may be 0.00 introduced if particles are sized according to their wet size which -0.04 -0.02 0.00 0.02 responds to humidity fluctuations (Kowalski, 2001), and similar 1/L [m-1] problems are caused by volatilisation or formation in the atmosphere which is discussed in more detail below. The exact effect on the unstable stable measurement depends on the setup and requires careful consideration: most previously reported submicron aerosol number fluxes Fig. 7.6. Summary of the dependence of aerosol deposition velocity on the Monin–

Obukhov length (L), indicating a sharp increase of normalized deposition velocity (Vd/u*) have relied on optical particle counting techniques that use closed in unstable conditions; from Pryor et al. (2008b), modified. path, high power active laser cavity scattering cells. Furthermore D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5237 most of these, but not all, adopt recycling dry particle free sheath air is applied to a chemically resolved (but not size resolved) particle flow with significantly lower RH than the ambient aerosol flow to ensemble, evaporation/condensation and/or heterogeneous chem- minimize contamination of the instrument optics. These instruments istry in/on particle surfaces could cause flux divergence. It can also therefore most likely provide a measure of the dry or partially dry modify fluxes if it leads to growth or shrinkage across the cut-off size particle size and not the ambient particle size. Hence measurements of the particle probe. Apparent emission fluxes with a CPC setup above of submicron particle fluxes reported in the literature are likely a grassland fertilized with NH4NO3, attributed these fluxes to aerosol representative of ‘‘dry or near dry aerosol deposition velocities’’ growth due to NH3 and HNO3 uptake and used the fluxes to derive of optical particle size and not the actual ambient deposition velocity, particle growth rates across the 11 nm cut-off of the CPC (Nemitz et al., whereas most large particle fluxes are likely a combination of both, 2008). This demonstrates that flux measurements can be used to infer some being derived from closed path and other open path instru- information on S and thus on aerosol processing, if the true deposition ments. Flux measurements using photometric techniques to deter- rate can be estimated independently. mine total PM2.5 and PM10 mass fluxes may not be subject to these The partitioning of species between the gas and particle phase is effects and for routine measurement of total mass fluxes e.g. for also associated with gas flux divergence (Soerensen et al., 2005) and network applications may be the most appropriate when combined can change the net rate of surface uptake of, for example, nitrate if with additional composition measurements. the deposition velocities of the gas and particle phase species differ Care needs to be taken that the inlet system does not respond in substantially (Pryor and Soerensen, 2000). The likelihood of flux a way that may be correlated with w. This could occur during non- contamination due to non-conservative behaviour can be estimated isokinetic sampling of coarse particles or during fast switching of using time-scale analysis (De Arellano and Duynkerke, 1992), and inlet flows in REA systems. There is also evidence that non-statio- can be quantified by deploying eddy covariance measurement narities may affect aerosol exchange particularly often (Fontan systems at multiple heights. et al., 1997). (i) Horizontal advection, due to the presence of large spatial 7.5.2. Relating measured fluxes to surface exchange: flux gradients in particle number, mass and/or composition. The divergence and the effect of chemical interactions importance of horizontal advection has been extensively A further uncertainty of the flux estimation with micro- evaluated in the carbon dioxide flux community (Baldocchi meterological techniques is that, although the local flux at the et al., 2001; Hong et al., 2008) and is likely to be important to, measurement height may be correct, it may differ from the actual but with few exceptions (Vong et al., 2004) the horizontal surface/atmosphere exchange. The most commonly applied form of advection term has generally been neglected in most particle the scalar conservation equation is (Pryor et al., 2008b): flux studies. The potential influence of horizontal advection can be quantified using a horizontally dispersed measurement array. (ii) The influence of non-local or ‘top–down’ processes in dictating vertical exchange. Observed scalar fluxes near to the ground are derived from two components: local surface-driven turbulence, Here term (1) is the local change in concentration, term (2) and non-local or ‘top–down’ processes such as entrainment of advection by the mean flow, term (3) represents the divergence of air from above the mixed-layer which can cause fluxes that are the turbulent flux, term (4) vertical transport by diffusion, term (5) counter to local gradients (Holtslag and Moeng, 1991). The vertical transport by sedimentation and term (6) concentration importance of non-locally induced turbulence in dictating changes due to sources or sinks. observed fluxes has been documented in gas exchange studies Methods of estimating particle (and other scalar) fluxes at the (Gao et al., 1989), but received less attention in the aerosol air–surface interface have typically relied on the assumptions of community, despite evidence that it plays a substantial role in horizontal homogeneity, steady state, the absence chemical source dictating flux magnitudes and may provide an explanation for or sink of the scalar, that the constant flux layer assumption applies upward fluxes in environments that have traditionally been to the lowest tens of meters above the surface (Businger et al., viewed as solely particle sinks (Pryor et al., 2008a). The potential 1971), and that the turbulence responsible for transporting the influence of ‘top-down’ processes on observed near-surface scalar of interest is locally induced (Monin and Obukhov, 1954; fluxes can be identified using scalar correlations (Sempreviva Monin and Zilitinkevich, 1974). However, as described in this sub- and Gryning, 2000) and quadrant analysis. section, there are multiple causes of flux divergence (i.e. that the flux observed at some height above the surface is not equal to that With the advent of techniques to measure compound-resolved at the surface). Three dominant sources of particle flux divergence aerosol mass fluxes, there is growing evidence that particle depo- þ are described below along with methods for their identification and sition velocities of NO3 and NH4 to semi-natural vegetation tend to 2 quantification: exceed those derived for SO4 or from particle number flux Non-conservative behaviour of the scalar under study (i.e. parti- measurements (Nemitz et al., 2004b; Thomas et al., 2009)(Fig. 7.7). cles) due to the interaction of other particle dynamics processes with the The deposition rate of these compounds measured over heathland vertical exchange ði:e: Ss0Þ.ThedegreetowhichS deviates from 0 (i.e. and forest greatly exceed those predicted theoretically for short and the magnitude of the vertical flux divergence due to phase transitions) tall vegetation, respectively (Fig. 7.2). The likely cause is evapora- is determined by; the chemical climate (Nemitz and Sutton, 2004; tion of NH4NO3 near the ground during the deposition process, Nemitz et al., 2004b; Sutton et al., 2007), particle ensemble (Pryor and where thermodynamic equilibrium favours the gas phase, due to Binkowski, 2004), and specific aspect of the particle ensemble being the depletion of NH3 and HNO3 by deposition of these reactive observed. If Eq. (3) is applied to consideration of the mass of the entire gases to foliar surfaces and warm surface temperatures. Thus, the particle ensemble, then only mass transfer (i.e. evaporation and/or flux measured well above the canopy is not limited by the physical condensation) can result in flux divergence. While if Eq. (3) is applied interaction of the particles with the vegetation surface, but reflects to a size-resolved number particle ensemble for any given particle the evaporation sink in the airspace above. This is supported by diameter, could Ss0 derive from concentration changes resulting the fact that the relationship between Vd and u* does not differ from nucleation, coagulation, and condensation/evaporation. If Eq. (3) between surfaces (Fig. 7.7), which implies that turbulent transport 5238 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

40 be large (Nemitz et al., 2002a). Often important parameters (e.g. + NH4 to heathland (Nemitz et al., 2004) leaf dimensions) are not provided in the scientiﬁc papers to provide - NO to oak forest (Thomas, 2007) 3 the input parameters to apply the models to the measurement 30 datasets. Thus there is an urgent need to harmonise ﬂux measurement approaches as much as possible and to provide guidance for auxiliary parameters that should be measured and provided with the measurement datasets to maximise their potential for model 20

[mm/s] evaluation. d V 7.6.1.2. Improved measurements in the accumulation mode. There 10 are still significant gaps in observations, particularly with respect to the critical size range associated with the transition between Brownian and turbulent impaction dominated particle capture 0 regimes. This size range is still poorly resolved by eddy covariance 0.0 0.2 0.4 0.6 0.8 1.0 techniques (w0.5 < Dp < 2 mm) as a consequence of few measure- u * [m/s] ments being available by any suitably characterized techniques and the large errors associated with these. The predicted minimum in Vd Fig. 7.7. Apparent nitrate and ammonium deposition velocities derived from chemi- as a function of size in this transition regime can vary widely cally speciated micrometeorological flux measurements. The large values are indicative of an additional loss of ammonium nitrate near the surface, due to evaporation. between different models (Fig. 7.5) and this will have significant consequences for long-term integrated dry deposited mass fluxes. This is therefore seen as a key area in need of attention by both (which scales with u*) is the main constraint on the flux. Since NH3 models and field observations. and HNO3 deposit to semi-natural vegation much more effectively than NH4NO3 aerosol, this shift to the gas phase increases 7.6.1.3. Understanding the effect of stability and leaf properties on the deposition rate of total ammonium and total nitrate. Since this deposition velocities. Another serious issue is the lack of any evaporation only occurs close to the canopy, it represents a non- detailed testable hypothesis in models explaining the link between resolvable (sub-grid) process in traditional transport models. increasing Vd and atmospheric stability and which most measure- Future parameterisations of Vd should account for this additional ments have reported in the literature for particle sizes Dp < 0.5 mm, sink for highly volatile aerosol components. most clearly seen for Aitken and small accumulation mode sizes. So far there are no wind tunnel studies of aerosol deposition to 7.5.3. Interpretation of measurements for model verification vegetated surfaces that take account of atmospheric stability and Deposition is effectively a number dominated process which, is these are needed to allow further model development. Studies of the subject to large uncertainties. Mapping from number to mass space hydrophobicity and anti-adhesion of non-smooth leaf surfaces show requires detailed knowledge of composition, size, shape and hygro- that the morphology of plant epidermal cells and the morphology scopicity. The hygroscopicity of aerosols can potentially generate the and distribution density of epicuticular waxes significantly affect largest uncertainty, not just in the measurement, but also in inter- their hydrophobicity and anti-adhesion properties and potentially preting the measurements. For example, the size at which a particle the adhesion of aerosol particles following impaction and inter- interacts with the vegetation surface often differs from its actual size ception, Ren et al. (2007). The microstructure of plant surfaces has at the measurement height, which again may differ from the size been well documented but an interesting phenomenon which might reported by a given instrument (dry vs. wet; geometric vs. optical have potentially serious implications for some studies of dry and wet diameter etc.). Most previous studies of deposition have not deposition is the so-called self-cleaning mechanism of some leaf been sufficiently complete to address any of these uncertainties structures (referred to as the ‘‘Lotus Effect’’). Some plant leaves are with respect to a complete closure of aerosol number and mass for completely lacking in microstructures while others can have sunken model comparison through use of growth factors. As a consequence, or raised nervatures which as a consequence cause super hydro- size-segregated and chemically speciated eddy covariance (and phobic behaviour. This in turn leads to a remarkable self-cleaning related) aerosol flux measurement techniques cannot currently process whereby fog droplets e.g. rolling down the leaf surface pick provide unambiguous results of particle number or mass fluxes to up aerosols and remove them from the leaf surface. Experiments surfaces as a consequence of fluctuations in aerosol size distributions whereby leaf surfaces have been artificially contaminated with on timescales that can lead to sampling biases. This sampling radioactively tagged aerosols and then subjected to artificial fog ambiguity and the potential for bi-directionality in aerosol fluxes droplets have been used to determine the retention rate of aerosols limit the accuracy with which Vd can be determined and hence will to plant surfaces and these can range from over 90% to less than 10% hamper improvement in model mechanistic descriptions of particle depending on the species examined and which were linked to deposition to natural vegetated surfaces. differences in leaf microstructure and orientation (Neinhuis and Barthlott, 1997). Considering the many inherent uncertainties in field flux 7.6. Future research needs measurements more wind tunnel studies are needed under better controlled conditions of stability, surface morphology and aerosol 7.6.1. Deposition measurements and reporting composition. The question is how detailed should a model be to 7.6.1.1. Standardisation of eddy covariance approaches and data describe adequately the surface interactions with aerosols (whether analysis procedures. Comparisons between different measurement they be ‘‘dry’’ or ‘‘wet’’ aerosols)? And more importantly how can systems are currently made difficult by the diverse approach used to their importance be measured? What information should be measure the fluxes as well as to analyse and present the data. For reported on surface morphology for future model development in example, some authors have derived parameterisations of Vd(Dp) order to attempt inclusion of these effects in future? These questions averaging over the negative (deposition) fluxes only, while other are best tackled by revisiting wind tunnel studies coupled with authors have averaged over the entire datasets. The difference can modern particle measurement techniques. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5239

7.6.1.4. Filtering or accounting for chemical interactions and water variability however these have focussed on dust suspension and uptake. A particular aspect of the data processing is the correction for the subsequent impact on both horizontal and vertical dust mass aerosol dynamics due to water equilibration and/or chemical inter- fluxes, which can be considerable (Gillette and Chen, 2001). actions. A growing number of datasets indicates that size-segregated As deposition mechanisms for submicron aerosols are particle number fluxes are affected by chemical effects (Nemitz et al., controlled by turbulent interaction with surfaces, and are highly 2004a,b) and this is confirmed by the first results from the chemically sensitive to particle size and micro-scale structures, it is likely that resolved mass fluxes from the Q-AMS eddy covariance system, which deposition velocities too are also affected by surface anisotropy and indicates that often some chemical aerosol components may be the manner in which this links to the microstructure. The notion of emitted at the same time as others are being deposited. Although a mean aerosol deposition velocity in this context has little value some modelling studies have been successful in qualitatively (much as it is now thought to be for suspension fluxes) (Okin, 2005) reproducing the observations both for bulk chemical fluxes and size- and a probabilistic approach must be used. Unfortunately, unlike segregated fluxes (e.g. Nemitz and Sutton, 2004; Van Oss et al.,1998), dust emission mass fluxes, there are virtually no observations of the standardized operational procedures for correction have not yet been impact of sub-grid scale surface anisotropy on aerosol deposition. developed. Indeed, we do not currently have the strategies in place Initially, a theoretical model study could explore the likely impact to test whether a particular dataset may be affected by chemical of anisotropy on effective dry deposition rates, for example interactions. It is unclear whether correction procedures will ever be adopting the concept of a lateral cover parameter (l) as a measure sufficiently accurate to fully correct for these effects, given the small of the vegetative canopy area intercepted by the wind and its value of the deposition rates. contribution through surface drag to the surface roughness, from which an effective aerodynamic roughness length for the landscape 7.6.2. Deposition models can be calculated (1993). In parallel, as a first step to improving 7.6.2.1. Migration to a probabilistic approach. Comparison of understanding in this area (which has been relatively moribund for measured deposition velocities as a function of size with different some considerable time) (Pryor et al., 2008b) the community needs regional scale model descriptions show large differences. Hence, to collect high quality micrometeorological aerosol flux measure- unacceptable errors will very likely be incurred in annual cumulative ments over a number of different surfaces with very different mass deposition values. A detailed sensitivity analysis between anisotropic variability. The observations should focus on deter- different deposition schemes used in current regional models with mining the frequency distribution function, f(Vd (Dp)) of aerosol observations has not yet been undertaken. Given the large apparent deposition velocities. difference between measurements and model schemes, it may be more appropriate to move towards a probabilistic approach in deriving 7.7. Conclusions – aerosols deposition estimates, by exploring a range of possible solutions, together with statements on their probability. For this purpose, prob- After little progress in the understanding of surface/atmosphere ability density function distributions for aerosol deposition velocities exchange of aerosols in the 1980s and early 1990s, the development need to be developed which can be used to test sensitivities to these of novel instrumentation suitable for flux measurements has led to factors in regional transport and global climate models. new investigations into the surface exchange, extending micrometeorological flux measurements to the urban environment 7.6.2.2. Improvement of modelling approaches. New modelling and the sea. For example, new developments in mass spectrometry approaches compare favourably with the available measurement have enabled the first eddy covariance flux measurements of 2 database, with the caveats on the data quality mentioned above. aerosol components (NO3 ,SO4 and organics) above urban areas Fig. 7.5 demonstrates that the model of Petroff et al. (2007b) in and vegetation, providing new information on sources, sinks and particular appears to be successful, similar to earlier modelling results chemical processing, together with deposition rates of the accu- of Davidson et al. (1982).Bothmodelshaveincommonthatthey mulation mode and the potential of studying deposition rates in include a detailed description of the canopy morphology. This intro- relation to particle composition. Furthermore, size-segregated duces additional requirements for input parameters and further particle flux measurement approaches have now been extended to degrees of freedom for adjustments to make the model match the the sub-100 nm size range, providing the first data for model measurements. However, good agreement is achieved with measured evaluation. The first long-term flux measurements of total aerosol canopy characteristics, increasing the confidence in the modelling number provide increasingly robust datasets of removal rates. approach. However, the model of Petroff et al. (2007b) needs to be As more detailed flux measurements as a function of size and simplified for application in operational chemical transport models composition have become available, it is becoming clear that size- and standardized characterizations for the different vegetation classes segregated particle number flux measurements are often influenced need to be developed. by hygroscopic growth and chemical processing. This highlights the need to minimize or to filter/correct for these effects when the data 7.6.2.3. Impact of surface anisotropy on suspension & deposi- are used for model validation. Apparent upward fluxes have been tion. Spatial organisation of vegetation on sub-grid scales can used to study the formation of NH4NO3 or biogenic SOA formation. influence aerosol surface exchange properties by introducing Measured effective deposition rates of NH4NO3 to semi-natural significant perturbations to mean wind flows by altering the vegetation greatly exceed those of other aerosol compounds, indi- probability density functions for turbulence velocities above that cating that new sub-grid parameterisations need to be developed to surface which in turn can alter the magnitudes of aerosol surface account of the additional deposition mediated through the evapo- exchange fluxes. The impact of this surface anisotropy is often seen ration of volatile aerosol components (e.g. NH4NO3). in observations of dust suspension fluxes over surfaces where Theoretical developments demonstrate that models of dry elongated regions may occur which are free of vegetation (e.g. deposition need to account for canopy structure and small-scale Gillette and Chen, 2001). As a result of this, neighbouring surfaces, morphology. Existing models are now capable of reproducing selected which have the identical vegetative indexes, can produce dust measurements, but will need to be simplified for operational appli- fluxes that differ from one another by as much as a factor of 4–8 cation in transport models and incorporate effects of atmospheric (Okin, 2005). Recently models have been developed that capture stability. The data available for model validation are highly dispersed and demonstrate the importance of sub-grid cell isotropic spatial in terms of quality, approaches, diameter measured and auxiliary 5240 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 information provided. Harmonised approaches in data processing and Table 2 1 presentation are needed. More sensitivity studies and probabilistic Estimates of global N2O and CH4 budgets (Tg y ). a 1 b 1 approaches are needed to explore the range of possible deposition N2O source Tg N2O–N y CH4 source Tg CH4 y estimates. In addition, the potential of modelling concepts that Natural sources account for small-scale spatial variability (increasingly applied for Oceans 3.8 (1.8–5.8) Oceans 4 (0.2–20) resuspension) should be explored to estimate dry deposition. Here Atmosphere 0.6 (0.3–1.2) Termites 20 (2–22) a new series of targeted, high-quality wind-tunnel experiments, Soils 6.6 (3.3–9) Wetlands 100 (92–232) Othersc 21 (10.4–48.2) coupled with the improved measurement technology would help decrease remaining uncertainties. Anthropogenic sources Agriculture 2.8 (1.7–4.8) Rice cultivation 60 (25–90) Biomass burning 0.7 (0.2–1) Biomass burning 50 (27–80) 8. Ecosystem–atmosphere exchange of the radiatively Energy & industry 0.7 (0.2–1.8) Energyd 106 (46–174) e active gases – N2O and CH4 Others 2.5 (0.9–4.1) Ruminants 81 (65–100) Waste disposal 61 (40–100)

8.1. Introduction Total sources 17.7 (8.5–27.7) 503 (410–660)

Sinks Atmospheric concentrations of the three main greenhouse gases Stratosphere 12.5 (10–15)f Stratosphere 40 (32–48) g CO2,CH4 and N2O have increased since the industrial revolution in Soils 1.5–3 Soils 30 (15–45) the 18th century due to anthropogenic activities. Increased fossil fuel Tropospheric OH 445 (360–530) burning, land use change and the intensiﬁcation of agriculture Total sinks 14 (11.5–18) 515 (430–600) facilitated by the manufacture of synthetic nitrogen and conse- a Sources are estimates for the 1990s as provided by IPCC (2007), Table 8.7. quently population growth are the main causes. Increased fossil fuel b From Wuebbles and Hayhoe (2002). c combustion is the main cause for rises in CO2, whereas microbial Others ¼ marine sediments, geological sources and wild ﬁres. processes in soils, sediments, and waters and rumens of animals, are d Energy ¼ natural gas, coal mining and other fuel related sources. e Atmospheric deposition, aquatic systems, sewage. responsible for the bulk of the observed increased atmospheric CH4 f Hirsch et al. (2006). and N2O concentrations. In this section, current understanding of g Cicerone (1989). CH4 and N2O exchange at the surface, and especially of the biological processes, measurement methodologies and models, are reviewed. The wider consideration of the global biogeochemical cycles of these oceans, termites) are also large and dominated global emissions until trace gases are provided in outline for context only, as these would the 20th century (Table 2). Increased livestock production and fossil take the review substantially beyond the focus on surface–atmo- fuel use are the main reasons for the atmospheric increase of CH4 sphere exchange. (IPCC, 2007). Soils are are a minor sink for CH4 and accounts for approximately 6% of the global budget; the dominant removal

8.2. Global budgets of N2O and CH4 process for atmospheric CH4 is oxidation by OH, mainly in the troposphere.

Atmospheric N2OandCH4 concentrations have risen from background levels prior industrialisation from 270 to 320 ppb N2Oand 8.3. Biological sources of N2O and CH4 from 700 to 1782 ppb CH4 in 2006 (http://www.esrl.noaa.gov/gmd/ aggi/). Nitrous oxide concentration has increased at a relatively 8.3.1. The biology of production and consumption uniform rate, with a mean annual growth rate over the last 10 years of of N2O and CH4 in soils and sediments 1 0.76 ppb year (Hirsch et al., 2006). By contrast, the growth rate in Microorganims are the dominant sources of N2O and CH4 in the CH4 concentration has changed considerably since the early 1990s troposphere. A knowledge of the underlying processes and micro- from a steady monotonic increase of approximately 15 ppb year1 in bial community structure is essential to improve global estimates of the later decades of the 20th century until the early 1990s, following N2O and CH4. The main microbial reactions involved (nitrification, which annual rates of change varied between increases of denitrification, methanogenesis and CH4 oxidation) are ubiquitous 5 ppb year1 to decreases of a few ppb year1 (IPCC, 2007). These very to all live containing ecosystems and are all sensitive to anthro- large and inter-annual variations in CH4 concentration remain unex- pogenic activities (e.g. irrigation, drainage, fertilization) and plained and present an important challenge to the research commu- climate (temperature and precipitation). nity (IPCC, 2007). Nitrous oxide is a by-product of aerobic nitrification and an The global budget of N2O is constrained by the sink strength in the obligate intermediate in the denitrification pathway, and is emitted stratosphere and atmospheric increase (http://www.esrl.noaa.gov/ by both nitrifiers and denitrifiers. Production and consumption gmd/aggi); hence, the global source strength is 15. 8–16 Tg N2O– of N2O is regulated by oxygen partial pressure; nitrification is 1 þ Ny (Crutzen et al., 2008, Hirsch et al., 2006. Cicerone, 1989). additionally controlled by the concentration of NH4 , while deni- There are some indications that also soils may significantly act as sink trification is also controlled by availability of carbon and NO3 for atmospheric N2OandthatthesoilN2O reduction has decreased (Conrad, 1995). Denitrification is the main biological process within the last decades (Chapuis-Lardy et al., 2007; Conen and Neftel, responsible for returning fixed N to the atmosphere as N2, thus 2007). However, this is so far not considered in any global estimate. closing the N cycle (Philippot et al., 2009). This reduction of soluble The atmospheric increase is largely attributed to agricultural N to gaseous N represents a loss for agriculture, since it can deplete activity (Table 2). Natural sources of N2O, the oceans, tropical and the soil of NO3 , an essential plant nutrient. The denitrification N2O/ temperate forests and grasslands/savannahs, are unlikely to have N2 product ratio is variable, and N2O may even be the dominant end changed much since pre-industrial times except where land use product. However, denitrification also provides a valuable has changed significantly. ecosystem service by mediating N removal from NO3 polluted The CH4 budget is constrained by measurements of the major waters in sediments and other water-saturated soils (Mosier et al., 13 1 sources and d C signature to a global total of 430–600 Tg y 1998). Denitrifiers can be sinks for N2O. Sink activity appears to be (Wuebbles and Hayhoe, 2002, IPCC, 2007). Anthropogenic sources stimulated by low availability of mineral N (Chapuis-Lardy et al., contribute 70% of the total budget. Natural sources (wetlands, 2007; Conen and Neftel, 2007). D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5241

Methane is produced by methanogenic archaea in anaerobic soil countries, principally northern Europe, the USA, Canada and Japan. (Philippot et al., 2009). The organisms require low redox conditions For N2O, studies on N fertilized agricultural soils dominate and for as well as on the fermentative production of precursors for the CH4 studies on rice paddy fields and northern wetlands. Studies methanogens. The main terrestrial CH4 sources are wetland ecosys- from Asia, where N demand is increasing at a faster rate than tems, where both methanogens and methanotrophs are present and elsewhere, are now emerging. There are insufficient data from active. Methane is consumed by methanotrophs active in the aerobic agricultural systems in Central and South American and African layers of most soils; undisturbed soils are largest CH4 sinks. countries, from new emerging cropping systems, especially biofuel crops, and land use change in temperate as well as tropical countries 8.3.2. Distribution of active microbial populations in soils to provide the detailed understanding required for model validation Although many different microbial species can produce and and for inclusion in emission inventories. consume N2O and CH4, information on the microbial biodiversity can provide useful insight into the health and functioning of the soil. The 8.3.4. Plant-mediated transport and production of N2O and CH4 development and recent automation of molecular methods have The general view is that soil-based microbial production and made it possible to characterise the abundance and function of soil consumption of CH4 and N2O are the major processes involved in microbial populations relatively quickly. One of these methods is the regulating biosphere–atmosphere exchange of these two green- analysis of the Phospholipid Fatty Acid (PLFA) composition of the house gases. Based on this perception, and combined with the lack microbial membrane (Bach et al., 2008). The method, together with of appropriate methodologies, our current knowledge about their analysis of microbial biomass carbon, Gram staining, N mineraliza- exchange rates is almost exclusively based on observations ach- tion rates, N2O, NO and CH4 fluxes, was applied to soils from arable, ieved using shallow, soil anchored enclosures. For many ecosystems grassland, wetland and forest ecosystems from the main climate such enclosures may exclude the vegetation (e.g. tall crops and zones in Europe as part of the NitroEurope Project (http://www. forests) and biases in emission estimates through omission of the nitroeurope.eu). The PLFA composition provided an overview on pathway through tall vegetation may result from this methodology. the distribution of functional microbial groups in soils of different It is well documented that soil–atmosphere transport of both landuses. There was a good separation between microbial commu- CH4 and N2O is mediated by aerenchymatic wetland herbaceous nities from wetlands and forests, but a closer similarity between species such as rice (e.g. Yan et al., 2000). Mangrove prop roots and microbes from grasslands and croplands (Fig. 8.1). The ratio of two also wetland and flood-tolerant trees have been shown to mediate marker PLFAs, cyclic fatty acids and precursor monounsaturated CH4 and N2O transport from the soil to the atmosphere, e.g. through fatty acids, is an index of bacterial stress. In this study, the stress the bark of black alder or from hybrid poplar seedlings (McBain parameter correlated with soil NO emissions and these were related et al., 2004), but only under conditions when the root zone was to N-deposition rates and soil acidity (Pfeffer et al., personal exposed to above ambient concentrations of the gas. communication). N2O emissions correlated positively with the The role of non-aerenchymatic plants and in particular trees in abundance of gram-negative bacteria, potential N-mineralization the exchange of CH4 and N2O between the soil–plant system and the rates and microbial biomass carbon. This can be explained by the fact atmosphere has only been sparsely investigated. Recent investiga- that gram-negative bacteria contain many microbial groups impor- tions, however, have emphasized a non-negligible role of vegetation tant for the N-cycle, such as nitrifiers, free-living N2-fixers and in the biosphere–atmosphere exchange of greenhouse gases. several denitrifiers. 8.3.4.1. Methane from vegetation. In 2006 Keppler et al. reported 8.3.3. N2O and CH4 fluxes from the main global ecosystems a very surprising observation that higher plants had the capability to Biosphere atmosphere exchange of N2O and CH4 has been emit CH4 under aerobic conditions with a mean emission rate of 1 1 studied for over 30 years. The data available are biased towards the 374 ng CH4 g dw h . From their findings they calculated a global 1 1 large N2O and CH4 emitting ecosystems in highly developed CH4 source strength of 62–236 Tg y for living plants and 1–7 Tg y for plant litter, the sum of which equals c. 10–40% of the total global CH4 source strength. Methyl-ester groups of pectin, an abundant polysaccharide in cell walls of non-woody plant tissue, served as aprecursorforCH4 (Keppler et al., 2008). UV light appears to be important in emissions of CH4 from plant material. Vigano et al. (2008) demonstrated that in the absence of UV light CH4 was not produced until the temperature reached 70–80 C; with UV light emissions were significant already at room temperature with rates up to 1 1 67 ng CH4 g dw h . McLeod et al. (2008) provided further evidence that not only CH4 but also ethane, ethylene and CO2 are produced from methyl-ester groups of pectin under UV irradiance, and that reactive oxygen species (ROS) arising from environmental stress may have aroleintheformationofCH4 from pectin. By contrast, Dueck et al. (2007) observed no significant CH4 emissions from photosynthesizing or dark respiring leaves, adding evidence to speculations that plant derived CH4 originates from abiotic processes. While processes generating CH4 within on on the surfaces of vegetation have clearly Fig. 8.1. Principal component analysis of microbial communites, determined as PLFAs been identified, the up-scaling to large areas and to the global atmo- (nmol g1 soil dry weight) of 13 NitroEurope sites representing different landuses. sphere remains largely speculative and have not therefore been Abbreviations: AM: arbuscular mycorhiza fungi; Sites: Forests: FI-Hyy ¼ Hyytia¨la¨, FIN; shown to contribute significantly to the global inventory. DK-Sor ¼ Sorø, DK; NL_Spe ¼ Speulder Bos, NL; DE-Hog ¼ Ho¨gelwald, DE; grasslands: UK-Ebu ¼ Easter Bush, UK; CH-Oen ¼ Oensingen, CH; HU-Bug ¼ Bugac, HU; croplands: 8.3.4.2. Nitrous oxide from vegetation. In a number of experiments, DE-Geb ¼ Gebesee, DE; FR-Gri ¼ Grignon, FR; IT-Cas ¼ Castellaro, I; IT-BCi ¼ Borgo Cioffi, I; wetlands: FI_Lom: Lompoloja¨nkka¨, FIN; UK-Amo ¼ Auchencorth Moss, UK; especially crops, plant-mediated emission of N2Ohavebeenobserved. 2 1 Figure provided by B. Kitzler and M. Pfeffer (BWF, Austria). Chen et al. (1999) found N2Oemissionsupto2.8mgm d from the 5242 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 plants in a soil–rye grass (L. perenne) system, and plant-mediated N2O and CH4 fluxes and their control by physical, chemical and micro- emissions from maize, soybean and wheat contributed up to 11,16 and bial processes has largely arisen from flux chamber measurements. 62% to the total sum of N2O emissions, respectively (Zou et al., 2005). In Recent development of high frequency instruments, that detect contrast, Mu¨ller (2003) found that presence of plants in old grassland very small concentration changes, has improved our knowledge of could induce N2O uptake. However, these studies did not identify the N2O and CH4 biosphere atmosphere exchange at the field/land- mechanisms underlying the plant based N2O production or reduction scape scale and at a high temporal resolution. processes. Chang et al. (1998) observed that barley (Hordeum vulgare) and oilseed rape (Brassica napus)emittedN2Ofromtheshootsupon 8.4.1. Flux chambers irrigation with water containing N2O,andhypothesizedthatN2Owas Usually closed (non-steady state) chambers are used for N2O conveyedbytheplantsfromthesoiltotheatmosphereviathetran- and CH4 flux measurements, e.g. Butterbach-Bahl et al. (1997), spiration stream. In contrast, Smart and Bloom (2001) found that N2O Conen and Smith (1998). Advantages of chambers over microme- emissions from wheat (Triticum aestivum) leaves was correlated with teorological techniques are that chambers are low cost and can be leaf NO3 assimilation activity. They found that N2O was formed during used on small fields/plots. Disadvantages include limited spatial in vitro NO2 -reductase activity of the leaves and suggested that N2O averaging of a spatially variable quantity due to small area (usually formation during NO2 photo-assimilation could be an important <1 m) of most of these enclosures. Recent developments in 15 15 global biogenic N2O source. Conversion of NO3 to N2Oinarangeof chamber methodologies include: aseptically grown plant species was reported by Hakata et al. (2003), and increased N2O emission from soybean was observed concomitant 1) an inter-comparison of the main chambers types employed for with an herbicide induced accumulation of plant NO2 (Zhang et al., N2OandCH4 chambers used within the European community 2000) providing further evidence for in planta production of N2O. (Philatie personal communication 2008), similar to the inter- The potential for tree species to act as conduits for N2O emis- comparison of soil respiration chambers (Pumpanen et al., 2004). sions were demonstrated in the work by Pihlatie et al. (2005).In ACCENT has contributed towards the funding of this exercise; a laboratory experiment with beech (F. sylvatica) seedlings it was 2) the validity of the commonly used linear regression equation to 15 15 15 found that fertilization with N-ammonium-nitrate ( NH4 NO3) calculate fluxes from non-steady state chambers was ques- 15 induced foliage N2O emissions and exposing the beech roots to tioned, as it may underestimate the true flux. An exponential elevated N2O concentrations induced significant emissions of N2O approach may be more accurate (Kroon et al., 2008), from shoots and leaves (Fig. 8.2). Pihlatie et al. also found that 3) development of the fast box method (Hensen et al., 2006) concentrations of dissolved N2O in leaves in a beech forest canopy facilitates chamber measurements from many spots within the exceeded ambient atmospheric concentrations, indicating a poten- field and establish a picture of the spatial heterogeneity of N2O tial for canopy N2O emissions. and CH4 emissions very quickly. This method requires In summary, substantial evidence exist that plants contribute combining manual chambers with sensitive fast response directly to the emission of CH4 and N2O. Yet, most work has been analysis of N2O and CH4, for example using tunable diode laser based on small-scale laboratory work and the scale of the fluxes techniques. appears small. However, there is an urgent need for field-based measurements and more detailed explanation of the underlying processes. 8.4.2. Micrometeorological methods ThedevelopmentoftunablediodelasersforCH4 and N2Oprovides 8.4. New developments in measurements of N2O a method of measuring N2OandCH4 biosphere atmosphere exchange and CH4 and denitrification by micrometeorological methods at high temporal frequency (30 min) over surfaces where fluxes are reasonably large (approx 20 ng m2 s1 N2O and CH4 fluxes are measured at scales ranging from a few of N2OorCH4). This measurement approach is particularly valuable for grams of soil to several km. Each scale and method has contributed heterogeneous ecosystems, i.e. grazed grasslands, and soft surfaces, to our current understanding of biosphere atmosphere exchange of where compaction by walking to a flux chamber may release gases N2O and CH4 (Denmead, 2008). Our global understanding of N2O intothechamber,e.g.peatwetlands or dung heaps. Eddy covariance measurements of CH4 for example were made over northern wetlands in Finland (Rinne et al., 2007)andofN2Oforexampleovergrazed grasslands in Scotland (Di Marco et al., 2004). For well-defined point sources, such as manure heaps and landfill sites the Gaussian plume method has been used to calculate the emission strength, by either walking or driving through the emission plume (Skiba et al., 2006; Hensen et al., 2006).

8.4.3. Comparison of eddy covariance with chamber methods Scaling up to the field and regional scale is usually based on data from small flux chambers. Several studies have been conducted to establish the validity of this approach. It is interesting that for N2O fluxes from grasslands and arable soils (Christensen et al.,1996) chambers strategically placed within the footprint of the micrometeorological tower are in reasonable agreement with eddy covariance. However for CH4 fluxes from rice paddies discrepancies of a factor of 2–3 between chamber and micrometeorological method, the chambers giving lower emissions, were reported Fig. 8.2. Nitrous oxide emissions (mgNO–N m2 h1) from beech (Fagus sylvatica) 2 by Kanemasu et al. (1995) from the Philippines and Hargreaves leaves after exposing the beech roots to different concentrations of N2O in the root compartment solution. Bars indicate average (þSE) of two different beech seedlings. (personal communication) from a rice paddy field in the Po Valley, Modified after Pihlatie et al. (2005). Italy. These different observations suggest that more comparisons D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5243 need to be carried out and that chambers may well be suitable unfortunately microbial populations have a larger impact on the for relatively firm surfaces, but not those of low bulk density or isotopic and isotopomer signatures of N2O than the production complete waterlogged. pathway itself (Sutka et al., 2003). Very recently, the 15Nisotopic abundance of soil-emitted NO was determined for the first time 8.4.4. Recent methodological advances in measurements (Li and Wang, 2008). The authors found very 15N-depleted NO with of total denitrification rates d15N values down to 50& and could identify both nitrification and For a full understanding of the processes and accurate simulation denitrification as sources of soil-emitted NO. of observations using models, we need to know the removal rate of It is concluded that many challenges of quantifying total deni- N2O in the ecosystem. The only natural process of permanent trification and differentiating between N2O produced by nitrifica- removal of excess N from ecosystems is denitrification to N2.The tion or denitrification remain. very high natural background of atmospheric N2 hampers direct quantification of total denitrification. A wealth of methods has been 8.5. Modelling of N2O and CH4 fluxes at site and regional scales: developed in the past decades for quantification of total denitrifi- approaches, applications and uncertainties cation (Groffman et al., 2006). Unfortunately, none is without drawbacks and even today, there is no method that can be used at Signatory states to the United Nations Framework on Climate the field scale or at high temporal resolution. The most common Change (UNFCC) are required to produce annual national inventories method is the acetylene inhibition method (Balderston et al., 1976), of greenhouse gas emissions from all anthropogenic sources, by which the terminal step of denitrification, i.e. the reduction of including emissions from soils. With regard to CH4 and N2O, soils are N2OtoN2 is inhibited by acetylene. Major drawbacks are that it is not the main sources in their respective global atmospheric budgets. The easy to achieve 100% diffusion of C2H2 to the active denitrification IPCC (2006) recommends three different approaches (Tier 1–Tier 3) to sites, that nitrification is also inhibited by C2H2 and that C2H2 provide emission inventories. Tier 1 represents the simplest way to interacts with NO in oxic environments (Bollmann and Conrad, model or estimate GHG fluxes on site and regional scales. It is a purely 1997). To overcome these problems a completely new concept of statistical approach, relating e.g. soil N2O emissions to the amount of replacing the background N2 during soil core incubations with applied fertilizer. In the 2007 IPPC reporting guidelines (IPCC, 2006) a noble gas (e.g. with a He:O2 mixture) has been developed and the default emission factor for direct N2O losses from soils following facilitates direct measurements of N2O and N2 (Scholefield et al., N fertilization is 1%. However, even if one assumes that this factor is 1997; Butterbach-Bahl et al., 2002). The major drawback is the high representative on a global scale, which has been questioned in the capital investment in equipment and the time-consuming flushing recent past (Crutzen et al., 2008), a fixed emission factor cannot procedure to remove N2. consider reported effects of climate, management or soil properties The use of stable isotope analysis either in tracer studies with on the magnitude of GHG exchange. Therefore, based on a detailed isotopically enriched tracer compounds or at the natural abundance survey on reported soil N2Oemissionsworldwide,Stehfest and level offer promising alternatives, but very little progress has been Bouwman (2006) developed a more detailed statistical approach for 15 made in the last 5 years. Application of NO3 containing fertilizer calculation of emission inventories, which also considers general 15 and monitoring N-labelled N2O and N2 provides a suitable tracer environmental factors such as climate, texture and soil organic carbon for denitrification to N2 for agricultural N fertilized soils, but not in contents and management related factors such as fertilization rates N-poor environments. For these 15N tracers can artificially stimulate and crop types. However, beside the fact that the demand on required N turnover, microbial immobilisation or dissimilatory reduction of input information is much larger, this approach also has its weak- þ NO3 to NH4 . For N-poor environments natural abundance of N and O nesses: a) the high uncertainty of the developed statistical model, isotopes may offer an alternative, as due to kinetic isotope frac- b) the rough classification scheme (which is due to the limited tionation the intermediates and the end product of denitrification availability of field datasets describing GHG emissions for different become increasingly depleted in 15N, whereas the remaining environmental conditions) and c) incomplete coverage of pulse 15 18 soil NO3 becomes increasingly enriched in N and O. If substrate is events, which may dominate annual site budgets. not limiting, large kinetic N isotope fractionation factors of up To account for the huge spatial and temporal variability of GHG to 40& can be observed during denitrification (Groffman et al., fluxes on site to regional scales the development and use of process- 2006). However, if denitrification is limiting or rates are small, as in oriented models may at present be the most promising approach the case for N-poor ecosystems, the apparent N isotope fractionation (Butterbach-Bahl et al., 2004). These models simulate the GHG is too small to provide unambiguous interpretation of the data. exchange at a given site based on the underlying processes, i.e. by 15 18 Dual-isotope labelling with N and O-enriched NO3 can simulating the dominant physico-chemical, plant and microbial identify nitrification or denitrification as source of N2O; this infor- processes involved in ecosystem C and N cycling and associated GHG mation is desirable for the models (Wrage et al., 2005). However, exchange (Li et al., 2000). As a general assumption, one defines there are problems. At low pH NO2 , intermediate of nitrification that the controlling factors for e.g. microbial C and N turnover such and denitrification, rapidly undergoes O-isotope exchange with as temperature, moisture and substrate responses, are comparable water (Casciotti et al., 2007). This O-isotope exchange might lead to across different climatic zones and landuses and that by capturing misinterpretation of the results when stoichiometric relationships the major biogeochemical processes within an ecosystem it is in the different N2O formation pathways are assumed, and is very possible to predict the temporal variability of fluxes. Such models likely the cause of O-isotope exchange between N2O and water, as require a thorough process understanding of the coupled C and reported by Kool et al. (2009). N (P) cycles, even though the level of process description may vary The most recent approach of quantifying denitrification rates and between the models currently in use (e.g. Li et al., 2000). However, differentiating between nitrification and denitrification as sources of these models also have the drawback, that modelling of ecosystem N2O is the analysis of N2O isotopomers. Intramolecular physico- processes involves a huge dataset of parameters needed to describe chemical site differences between terminal and central N atom lead heat transfer, water movement, plant and microbial growth or to differences in N isotope ratios between the two positions during anthropogenic management. In comparison to statistical approaches N2O formation and consumption. Differences in this so-called mechanistic models often show an improved performance with 15 N site preference have been attributed to N2O production during regard to reproducing observed differences in GHG fluxes between nitrification and denitrification, respectively (Pe´rez et al., 2001), sites, seasons and management practices (e.g. Kesik et al., 2006). 5244 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

However, the increasing use of mechanistic models also shows This is a shortcoming, which needs to be properly addressed in that we still need to improve our process understanding, e.g. the future work. Nevertheless, biogeochemical models offer a great regulation of microbial processes and its dependence on microsite opportunity to improve our understanding of ecosystem processes variability of environmental conditions such as redox potential or and GHG exchange and they will play an important role in identi- the feedback of temperature on organic matter decomposition. fying and predicting consequences and feedbacks of global changes A good example of the deficiencies in understanding N2 vs. N2O (climate and land use change) for ecosystem functioning and production during denitrification is provided by (Groffman et al., biosphere–atmosphere trace gas exchange. 2006). This gap in knowledge also precludes the parameterisation of the denitrification process in biogeochemical models such as 8.6. Validation of models by landscape and regional DNDC or DayCent, which in consequence leads to a systematic scale measurements underestimation of N2 losses using either model. Biogeochemical process models have recently been used in Developments in inverse modelling and direct large-scale a number of studies for calculating regional soil GHG emission measurements provide very powerful tools to constrain and verify inventories (Fig. 8.3). Thereby regionalisation is achieved by our bottom up models and inventories. For example, Bergamaschi coupling of the models to GIS databases holding all the relevant et al. (2005) compared inverse models with national bottom–up information needed for initializing (soil and vegetation properties, inventories for CH . These developments are taken further within management) and driving (meteorological conditions) the models 4 the NitroEurope project (www.nitroeurope.eu). (Kesik et al., 2006). Such an approach partly neglects landscape The development of instruments sensitive enough to measure processes, such as e.g. lateral flow and transport of nutrients and very small concentration differences has made it possible to sediments via leaching or erosion. An increasing number of groups directly measure CH and N O concentrations from aircraft and are working on fully coupled landscape models, which do allow 4 2 satellites. For example, in the UK aircraft based N O and CH consideration of interactions between the biosphere, hydrosphere 2 4 concentrations measurements downwind of the British coast have and atmosphere at landscape scales. National inventories for N O 2 delivered unique measurements of CH and N O at the country and/or CH emissions from soils using DNDC or DayCent have been 4 2 4 scale and provided independent top-down estimates of UK emis- calculated for US, UK, China, Germany, India or Europe. Even on sions. Measurements were interpreted by using a simple boundary- a global scale, the GIS coupled Forest-DNDC model was used to layer budget approach and the dispersion model NAME. This estimate N O emissions from tropical rain forest soils (Werner 2 approach suggests that the bottom up national emission inventory et al., 2007). Increasingly biogeochemical models have been used to underestimates CH emissions by a factor of two and N O emissions study potential strategies for mitigating GHG emissions from 4 2 by a factor of three (Polson, submitted for publication). An under- soils on site as well as on regional scales (e.g. Li et al., 2006)orto estimation of the UK national CH inventory was also reported by improve our understanding how future changes in climate or land 4 Bergamaschi’s et al. (2005) comparison of bottom up and inverse use may feedback on biosphere–atmosphere exchange of GHG modelling approaches. (Parton et al., 2007). Uncertainty in such emission inventories and Satellite-borne instruments, such as SCIAMACHY, are able to mitigation/feedback studies is associated with the uncertainties in provide CH concentration measurements at the global scale. input parameters as well as with the uncertainties in model 4 SCIAMACHY can clearly detect spatial and temporal variations in parameters. However, in present studies the uncertainties in input CH concentrations in the boundary layer, a considerable achieve- parameters have mainly been addressed using Monte Carlo tech- 4 ment given the small enhancements in a large background signal. niques (Kesik et al., 2006; Werner et al., 2007), whereas model Using these methods emissions due to coalfields, rice cultivation, parametric uncertainty is often neglected (Van Oijen et al., 2005). ruminants and wetlands are visible for China and India and the Po valley in Italy (Buchwitz et al., 2005, 2006). Comparisons between SCIAMACHY observations of CH4 concentrations and those derived from simple emission inventories revealed large regional and seasonal differences, especially over tropical rainforests. To some extent these differences were caused by overestimating CH4 concentrations when water vapour concentrations were large (Frankenberg et al., 2008). With this correction, SCIAMACHY still estimates a larger CH4 budget for the tropics than previously estimated and is a clear priority for direct measurements at the surface using chamber and micrometeorological methods. Validation of the global N2O budget using satellites is currently not yet possible as sufficiently accurate and precise N2O satellite data with high sensitivity near the earth’s surface have not yet been obtained.

8.7. Conclusions

The key developments and gaps in knowledge are:

1. New molecular tools are now available to link soil microbial biodiversity with soil function and can provide an overview of the distribution of functional microbial groups in soils of different landuses, and assign trace gas emissions to the active microbial population. Fig. 8.3. N2O emissions from agricultural soils in Europe using the GIS coupled DNDC model. For further details on databases and methodology see Butterbach-Bahl 2. Instrument development has facilitated CH4 and N2Oﬂux et al. (2009). measurements at the ﬁeld and landscape scale and provides D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5245

long-term measurements at large spatial scale and high temporal resolution at key sites. 3. New methods to study denitrification rates to N2 and isotope studies to elucidate the microbial pathway responsible for N2O production and removal are being developed, but none of these methods can currently be used at the field scale or high frequency temporal scales. 4. There are insufficient data to scale up CH4 and N2O emissions to the global scale or to include ‘new’ crops, i.e. bioenergy crops. 5. There is a gap in knowledge of the contribution and quantification of plants, especially trees, in producing and transporting N2O, CH4 from soil to atmosphere. 6. Biogeochemical models have been developed and synthesize our understanding of ecosystem processes and GHG exchange. They play an important role in identifying and predicting consequences and feedbacks of global changes (climate and land use change) for ecosystem functioning and biosphere–atmosphere trace gas exchange. These models also provide mechanistic tools to up-scale emissions to regional and global scales. 7. Inverse modelling, tower and aircraft based boundary layer budget studies have been developed and now provide appropriate tools to challenge and validate bottom up inventories at

the regional and country scale. Fig. 9.1. A schematic diagram of the processes affecting organic species at the air–sea interface. 9. Exchange of trace gases and aerosols over the oceans

In this section, considering recent developments in surface– being ejected directly with primary aerosol from the sea surface atmosphere exchange over the oceans, the focus has been narrowed (Fig. 9.1). to organic trace gases and aerosols, in which there have been major Several important organic emissions from the ocean have recent advances in understanding. been identified previously. The best known is dimethyl sulphide (DMS) which is produced biogenically in the ocean (e.g. Keller 9.1. New trace gas interactions at the air–sea interface et al., 1989; Liss et al., 1997, and references therein), and yields the inorganic aerosol component sulphate upon complete Considering the size and potential importance of the air–ocean oxidation in the atmosphere (Kiene and Bates, 1990). It is also interface, it is surprisingly poorly characterized for most organic well established that organohalogens are emitted in various trace gases. These organic species are known to play important roles forms (e.g. methyl iodide, bromoform, methyl bromide) from in the Earth’s atmosphere, impacting ozone chemistry and aerosol phytoplankton, bacteria, molluscs and worms (e.g. Gribble, formation, thereby influencing the Earth’s overall oxidation capacity 1992). Following atmospheric oxidation, these can affect either and radiative budget (Williams, 2004 and references therein). tropospheric or stratospheric ozone, depending on the lifetime It should be noted that the net primary production (NPP) of the of the species. However, over the period of the ACCENT project ocean is comparable in size to that of the terrestrial biosphere (2003–2008), there has come a realisation that the surface ocean (ca 45 PgC yr1), even though there is approximately 100 times less can play an important role in the budgets of many more organic biomass in the ocean than on land. The relative paucity of ocean trace gases. For example, the surface ocean has been shown based data compared to terrestrial sites is due partly to accessibility recently to be a large reservoir for oxygenated organic species and partly to the high spatial and temporal variation within the e.g. acetone (Singh et al., 2003; Williams et al., 2004). The limited oceanic biomass. Moreover, there has been a perception from possible influence of oceanic isoprene on marine clouds has also earlier studies of oceanic alkanes and alkenes that the global ocean been hotly debated (Meskhidze and Nenes, 2006). Finally is a relatively minor source term. Over the period of the ACCENT a surface ocean source of methanol first speculated in mesocosm project, this view has changed remarkably and recent studies are studies has been implemented in a global model assessment of beginning to recognise the profound effects of the ocean–air inter- methanol, thereby generating an improved fit between model face on global chemical budgets. For many important chemical and measurement data (Millet et al., 2008). Therefore this article species in the atmosphere the role of the ocean remains the greatest has been focussed on the more recent discoveries related to uncertainty in the budget. acetone (CH3COCH3), methanol (CH3OH), isoprene (C5H8), The sunlit regions of the oceans are home to a myriad tiny monoterpenes (C10H16) and alkyl nitrates (RONO2) in order to plant species and bacteria. These organisms photosynthesise highlight the new developments in air/ocean interactions. carbon dioxide (CO2) from the atmosphere into biomass, and a fraction of the carbon ‘‘leaks’’ out into the surrounding seawater 9.1.1. Case studies in the form of organic compounds. Some small volatile species 9.1.1.1. Acetone (ocean uptake). Over the past 5–6 years our with low Henry’s Law coefficients are known to escape directly to understanding of the role of the ocean in the global acetone budget the atmosphere (e.g. dimethyl sulphide, DMS) while larger species has changed remarkably. Acetone is ubiquitous in the troposphere will remain in the water phase. Subsequent photo-oxidation in and found at relatively high mixing ratios (ca 200 ppt) even in both air and seawater phases generates a multitude of photo- the remote Pacific atmosphere. Since acetone is recognised as an chemical breakdown products. These compounds may affect the important precursor for PAN, ozone and HOx, especially in the cold, hygroscopicity and reflectivity of the marine boundary layer dry, upper troposphere, there has been interest in determining the aerosol, either by condensing onto existing aerosol surfaces, or by sources and sinks worldwide. In 2002, Jacob et al. published 5246 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 a global budget of acetone (Jacob et al., 2002) which differed from et al. (2005), the overall the sources and and sinks for acetone were all previous budget attempts in that it considered the role of the still not balanced. To understand these processes better a new ocean for the first time. Through inverse modelling, they estimated approach to investigate acetone ocean fluxes was made using that the ocean was an important net source of acetone. Indeed, so-called ‘‘mesocosms’’ (Sinha et al., 2007). The mesocosms are from the total global source of 95 Tg, some 25 Tg was estimated to light permeable Teflon tent-like structures which float on the originate from the ocean in order to balance the known sources and surface ocean enclosing a volume of air near the surface, and with sinks. This was pioneering work since at that time no seawater walls that extend some 20 m below the surface to restrict the acetone measurements, or air–sea fluxes were available. However, advection of the water mass below. The airspace in the top of the in the space of just two years this view changed dramatically. In mesocosm was continually flushed with ambient air to give a resi- 2004 the model developed by Jacob et al., 2002 was tested against dence time of approximately 3 h in contact with the water surface. measurements over the remote Pacific. It was found that the model By measuring at the inlet and outlet, the flux could be calculated consistently overpredicted the measured acetone mixing ratios in while phytoplankton in the water column were monitored. In the the marine boundary layer and the authors concluded that the case of methanol a clear uptake flux (from the air to the ocean) was ocean was a net global sink for 15 Tg, and that the sources and sinks observed throughout the experiment, whereas for DMS the flux were not balanced. In 2004, the first open ocean measurements of was always from the ocean to the air. Interestingly, for acetone the acetone in air and seawater were made (Williams et al., 2004). The flux was found to be variable but systematic. In strong daylight and interhemispheric gradients and depth profiles shown by Williams in the presence of significant biological activity, acetone was et al., 2004 were consistent with uptake of acetone from the air to emitted from the ocean to the air. In low light or biologically poor the sea and a microbial sink in the seawater. regimes, however, acetone was taken up by the water. These results In 2004, two important new publications emerged concerning are consistent with the results of Marandino et al., 2005 and the acetone. The first was a laboratory-based study which re-deter- ocean being a net sink for acetone on a global scale, since most of mined the photolysis quantum yield of acetone as a function of the ocean is oligotrophic. However, biologically active regions (e.g. temperature and pressure (Blitz et al., 2004). It was found that upwelling zones, ocean fronts, or large natural phytoplankton the accepted acetone photolysis rates were significantly over- blooms) can be strong sources in daylight and depending on their estimated by a factor ranging from 3 to 5, particularly for the size could to some extent offset the general sink. It is therefore cold, low pressure conditions of the upper troposphere. In the important to investigate these biological hotspots in future to same year, a new shipborne measurement study was published in better constrain the global budget (Fig. 9.2). which the authors directly measured the flux of acetone at the ocean surface for the first time using an eddy correlation method 9.1.1.2. Methanol (ocean uptake). In many respects the global (Marandino et al., 2005). Interestingly, the authors consistently methanol budget is similar to that of acetone discussed above. Plant found uptake fluxes (from the air to the ocean) for acetone over growth accounts for most of the estimated global source (40–80%) the oligotrophic Pacific ocean which became stronger further and again the role of the ocean is one of the largest uncertainties in the from the equator. For comparison Marandino et al., 2005 also budget. Studies of methanol have consistently indicated an ocean determined the flux of acetone by making separate measure- uptake of methanol (Williams et al., 2004; Lewis et al., 2005; Sinha ments in the seawater (5 m depth) and air (18 m height). Similar et al., 2007; Carpenter et al., 2004 and references therein.) Recently, to the results from the Tropical Atlantic (Williams et al., 2004), a global 3-D chemical transport model (GEOS-Chem) was used to these water and air measurements led to highly variable flux integrate and interpret newaircraft, surface, and oceanic observations results at the surface, whereas the direct flux measurement was of methanol in terms of the constraints that they place on the more consistent. This strongly suggested that for acetone, the atmospheric methanol budget (Millet et al., 2008). It was shown that actual air/ocean flux is being driven by processes in the upper- for methanol, although overall the ocean represents a net sink, most layer (0–5 m). a separate light dependent oceanic source needs to be introduced in Although these two new studies (Blitz et al., 2004; Marandino order to correctly simulate regional distributions in the atmosphere. et al., 2005) had a strong impact on the original budget of Jacob This in-water source has the effect of tempering the uptake flux

Fig. 9.2. MODIS chlorophyll picture of the Southern Atlanic Ocean in January, inset the Research vessel Marion Dufresne. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5247 particularly in the Tropics. It was deduced that that the ocean contains terrestrial sources. Maximum levels of 100–200 pptv total mono- a large primary source (85 Tg y1) of methanol to the atmosphere and terpenes were encountered when the ship crossed an active phyto- also a large sink (101 Tg y1), comparable in magnitude to atmo- plankton bloom, whereas over the oligotrophic ocean monoterpenes spheric oxidation by OH (88 Tg y1). Thus the ocean is a net sink were mostly below detection limit. The monoterpenes/isoprene overall, but the in-water source term must be included to match with ratio reached 21% in laboratory experiments (the ratio between the available atmospheric measurements datasets. highest production rates of total monoterpenes and isoprene) and ranged between 7 and 60% in the Southern Atlantic Ocean. 9.1.1.3. Isoprene (ocean emission). Isoprene, the strongest terrestrial biogenic emission, has also been observed as an oceanic emission 9.1.1.6. Alkyl nitrates (ocean emission). Alkyl nitrates were assumed (Bonsang et al., 1992) and in laboratory-based studies of plankton until recently to be exclusively of anthropogenic origin, being emitted (Shaw et al., 2003 and references therein). It has been suggested directly from combustion or chemical processes (Simpson et al., 2002), recently that marine isoprene emissions are the cause of cloud or being produced at low yield in the photo-oxidation of organic droplet radius changes in marine clouds situated directly over compounds in the presence of NOx via the reaction of an organic phytoplankton blooms (Meskhidze and Nenes, 2006). However, an peroxy radical (RO2)andNO(Roberts, 1990). However, measurements impact of the isoprene on cloud properties appears unlikely given of MeONO2 and EtONO2 both in equatorial air and seawater (Chuck that concentrations of isoprene measured over the Southern Oceans et al., 2002) have revealed positive saturation anomalies, and high do not impact the organic carbon aerosol concentrations signifi- levels of RONO2 which correlate strongly with species of known cantly (Arnold et al., 2004). In the aforementioned paper an aerosol marine origin such as bromoform (Blake et al., 1999). The mechanism production efficiency of 2% was assumed for isoprene, and the of formation of marine alkyl nitrates still remains somewhat unclear. modelled contribution of isoprene to organic carbon (OC) was found Production in seawater through aqueous phase photochemistry (Dahl to be less than a 1%. Moreover, since time is required to oxidise et al., 2003) has been shown to occur via the reaction of ROO þ NO, isoprene to nucleating products, a superpositioning of a cloud effect where photolysis of coloured dissolved organic matter (CDOM) over a bloom in a region of high wind speeds again appears unlikely. generates the peroxy radicals and nitrate (NO2 )photolysisgenerates Typical mixing ratios of isoprene over phytoplankton rich areas are the NO. Interestingly, the yield of the reaction ROO þ NO in seawater 200–300 ppt, approximately an order of magnitude less than over was found to be significantly higher than in the gas phase. Alterna- the rain forest (Williams et al., 2001). However, since isoprene reacts tively, alkyl nitrates may be emitted directly from marine biota, rapidly in air, terrestrial emissions will not impact the open ocean. although direct evidence for enzymatically mediated production has Marine isoprene emissions could influence the local ozone produc- not yet been found. Using a chemical transport model Neu et al. (2008) tion efficiency in regions where ship emissions of NOx occur. This found the maximum impact of the oceanic alkyl nitrates to be over the may be significant for fishing fleets, as the fish, and hence the fleet, Western Pacific, where they were responsible for of increase of up to follow the isoprene producing phytoplankton. 20% of the ozone column.

9.1.1.4. Halogenated organics (ocean emission and uptake). The ocean acts as a huge reservoir for chlorine, bromine and iodine and 9.2. Aerosols volatile organic halogen species (e.g. halocarbons) provide a pathway to transport halogens from the water phase to the atmosphere. Previous 9.2.1. Primary marine aerosol (PMA) source functions studies revealed that halocarbons like CH3Cl, CH3Br, CH3I, CHBr3 and Primary marine aerosol (PMA), or sea-spray aerosol is a major CH2Br2 are emitted from various marine organisms, especially macro- source of global natural aerosol mass budgets and is important for and microalgae, (Scarratt and Moore,1999 and references therein). The global climate. Mass is dominated by the super-micron size range global sources of CH3I, CH2Br2 and CHBr3 are dominated by marine and traditionally source functions have been derived in this size contributions. Algal emissions of halogenated compounds vary regime. The supermicon size range also contributes significantly to considerably, not only from species to species, but also as a function of aerosol scattering (Kleefeld et al., 2002) and optical depth (Mulcahy age, temperature, time of day, nutrition, partial desiccation, grazing, et al., 2008) and thus the direct climate forcing effect. In terms of the light and tidal movement (Ekdahl et al., 1998). Polybrominated species submicron size range, number concentration rather than mass (e.g. bromoform) are primarily emitted by macroalgae which occur becomes important in terms of the indirect radiative forcing effect only in coastal regions, whereas monohalgenated compounds can be through the production of cloud nuclei (O’Dowd et al., 1999). Only produced from various open ocean biomes. quite recently it has become accepted that submicron sea-spray aerosol exists, and as a result, submicron source functions are rela- 9.1.1.5. Monoterpenes (ocean emission). Recent laboratory incuba- tively new in terms of development. tion experiments and shipboard measurements in the Southern The PMA source function describes the flux of sea-spray aerosol, Atlantic Ocean have provided first evidence for marine production of i.e. the number of droplets produced per unit surface area and per monoterpenes (Yassaa et al., 2008). Nine marine phytoplankton unit of time, evaluated typically at 10 m above the ocean surface. monocultures were investigated using a GC–MS equipped with an Hence the function describes an effective flux, parameterised in enantiomerically selective column and found to emit at rates, terms of ambient parameters such as wind speed and water 1 1 expressed as nmol C10H16 (monoterpene). g [Chl_a] day ,from temperature. Measurements may provide total fluxes, i.e. the total 0.3 nmol g [chl_a]1 day1 for Skeletonema costatum and Emiliania number of particles in a given size interval, or spectral fluxes. huxleyi to 225.9 nmol g [chl_a]1 day1 for Dunaliella tertiolecta.Nine The latter are expressed in number of droplets for a range of size monoterpenes were identified in the sample and not in the control, intervals, i.e. mm1 m2 s1. In this review, we focus on a selection of namely; ()-/(þ)-pinene, myrcene, (þ)-camphene, ()-sabinene, recently developed or improved source functions which span both (þ)-3-carene, ()-pinene, ()-limonene and p-ocimene. submicron and super-micron sizes. Particular emphasis is focused The laboratory measurements are also supported by shipboard on the submicron spray flux and chemical characteristics. A measurements of monoterpenes in air were made between January comprehensive historical review, focused primarily on sea-salt and March 2007, while crossing the South Atlantic Ocean, see aerosol production, is provided by Lewis and Schwartz (2005) with Fig. 9.2. Monoterpenes were detected in air over high ocean chloro- some additions and description of specific source function formu- phyll regions sufficiently far from land as to exclude influence from lation in O’Dowd and de Leeuw (2007). 5248 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

It is often assumed that the dependences on droplet size and provides a water temperature dependence that compares favourably environmental parameters can be separated, i.e. the source func- with independent measurements (e.g. Clarke et al., 2006) for 25 C. tion is presented as the product of a size-dependent function, g(r), and a function that describes the parameterisation as function of of 9.2.2. Chemical composition of primary sea spray environmental parameters, f(a,b,.), where r is the droplet size Although the dominant mass fraction of sea-spray aerosol is sea- at a specified relative humidity (dry, RH ¼ 80%, or wet) and a, b, . salt, organic matter also contributes to the overall mass and it has are, e.g. wind speed, water temperature, atmospheric stability, etc. long been known that marine aerosols contain organic material Scaling arguments show that droplet production varies approxi- (i.e. Blanchard, 1964). Field measurements suggested a significant mately with the third power of the wind speed. However, other biogenic primary source of marine organic components (O’Dowd types of paramterization have been proposed as well. Selected et al., 2004; Cavalli et al., 2004). In particular a dominant water- source functions are shown in Fig. 9.3 for a wind speed of 8 m s1. insoluble organic fraction in fine marine aerosol collected during There are two main developments to report on: the first in terms of periods of phytoplankton bloom in the North Atlantic was observed the super-micron sizes where the data in Fig. 9.3 show that the and it was hypothesized that these insoluble organic components discrepancy between different formulations is much reduced with could have a mainly primary origin. Similar results supporting respect to the review situation reported by Andreas (2002). a biologically driven oceanic OC source have been recently reported With respect to Lewis and Schwartz (2004), the uncertainty has by Spracklen et al. (2008). been reduced by a factor of 2. For small particles a clear size The most comprehensive study to date on the organic fraction 1.5 dependence emerges varying roughly as r80 . The source functions of sea-spray aerosol has been conducted by O’Dowd et al. (2004). shown in Fig. 9.3 were obtained using different methods and They found a significant and dominating fraction of organic matter different physical principles but leading to consistent results. in submicron sizes, while the super-micron size range was The second main development is the extension of the source predominately inorganic sea-salt. It should be noted, however, function well into the submicron size range. The Mårtensson et al. that the absolute magnitudes of organic mass in the sub and (2003) laboratory-based study extended the size-resolved source super-micron size ranges were equivalent (with one-third of the function down to r80 ¼ 20 nm and found that the production as total organic mass residing in the coarse mode), and that it was a function of size was also dependent on temperature. Clarke et al. their relative concentrations that differed significantly. Fig. 9.4 (2006) provide a source function for particles down to 10 nm. These illustrates the chemical composition of clean marine aerosol over studies combine experiments in the laboratory or over the surf the north east Atlantic during winter and summer periods, zone, to determine the spectral shape of the flux, with whitecap corresponding to low and high biological activity periods (O’Dowd coverage which in turn is paramterized as function of wind speed. et al., 2004). Also shown is the distribution of chlorophyll- Direct and in situ measurements of sea spray total number fluxes a derived from the SeaWifs satellite. During periods of high (D > 10 nm) are provided by the eddy covariance (EC) method that biological activity, the organic fraction ranged from 40 to 60% of was first attempted by Nilsson et al. (2001) in the Arctic Ocean. The the submicron mass, while during low biological activity periods, advantage of this method, as opposed to the whitecap method, is the fraction reduced to about 10–15%. O’Dowd et al. (2004) argued that all particles within the detectable size range may be measured, that the water-insoluble organic fraction, dominating the organic and hence there is no restriction to bubble-mediated production. composition in the fine size fraction, was likely to be derived from The technique was also used at a coastal station over the North East bubble-mediated production. Atlantic by Geever et al. (2005), who quantified total number Later experiments, using the gradient technique to determine concentration over two size ranges covering the Aitken mode (10– aerosol chemical fluxes at Mace Head (Ceburnis et al., 2008) 100 nm) and the Accumulation mode (100–500 nm). showed that the water-insoluble organic carbon (WIOC) mass Overall, the most recent schemes agree quite well (e.g. Clarke invariably had an upward mass flux associated with it and followed et al. surf zone study compares very well to the Mårtensson et al. similar trends to sea-salt gradients, while water-soluble organic laboratory-based parameterisation), providing an improved level of carbon (WSOC) mass possessed a downward flux profile identical confidence in PMA source functions over sizes from 0.01 mmto to nss-suphate. They concluded from the gradients that WSOC must w10 mm. In addition, the Mårtensson et al. (2003) parameterisation be formed from secondary aerosol formation processes while WIOC must be formed from primary production. These conclusions were

108 further supported by Facchini et al. (2008) who conducted bubble- bursting experiments amidst a plankton bloom over the NE Atlantic 107 during the MAP (Marine Aerosol Production) cruise in 2006 (Fig. 9.5). During these experiments, it was found that spray 106 particles exhibited a progressive increase in the organic matter

-1 content from 3 0.4% up to 77 5% with decreasing particle s 105 -2 diameter from 8 to 0.125 microns (Fig. 9.5). Submicron organic matter was almost entirely water insoluble 104 Monahan et al 1986 (WIOM) and consisted of colloids and aggregates exuded by Monahan Extrapol phytoplankton. Facchini et al. (2008) found that the WIOC to sea- 103 Martensson et al., JGR, 2003 salt mass ratio ﬁngerprint as a function of particle size in the bubble

dF/dLog (r) m Vignati et al., JGR, 2001 tank experiments matched that observed in atmospheric samples 102 Gong, JGR, 2003 Clarke et al., JGR, 2006 both at Mace Head (shown in Fig. 9.5) and on the MAP cruise over de Leeuw et al., JGR, 2000 1 the open ocean. These results conclusively conﬁrmed that the 10 de Leeuw et al., AMS, 2003 Reid et al., JGR, 2001, WIOC component observed in marine air samples relate to primary 100 aerosol production. Electron microscopy observations of individual -2 -1 0 1 2 10 10 10 10 10 particles collected at the ocean surface in a number of sites sup- Radius (microns) port the hypothesis that complex exopolimers and the microgels Fig. 9.3. Compilation of sea-spray source functions. Flux values are for a wind speed of forming from these, produced by bacteria and algae, are involved in 8ms1. bubble-bursting processes (Bigg and Leck, 2008). D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5249

Fig. 9.4. (Left) Chemical and mass size distributions for North Atlantic marine aerosol during periods of low biological activity and high biological activity. (Right) oceanic chlorophyll-a concentrations over the North Atlantic for low and high biological activity periods.

These results indicate that a sea-spray source function should et al. (2005) accumulation mode number flux, combined with not only consider size-resolved mass, but also chemical composi- the Yoon et al. (2007) seasonal modal diameter (minus secondary tion. The first attempt at a combined submicron organic-inorganic aerosol mass), and integrated with the seasonal trend in WIOM/sea- sea-spray source function, implemented in a regional climate mode, salt ratios to produce a physico-chemical flux function driven by was produced by O’Dowd et al. (2008). They combined the Geever wind speed and satellite-derived chlorophyll-a concentrations over

Fig. 9.5. (Left) Average chemical composition relative concentration from bubble-bursting tank samples. (Bottom) average ratio of WIOC to sea-salt from atmospheric samples at Mace Head. Data for the 0.06–0.125 mm size range are not reported from the bubble tank because the total carbon analyses in this stage were below detection limit. The bars are the standard deviation of the mean. (Right) Visible satellite image of plankton bloom off the west coast of Ireland during the MAP cruise June–July 2006. Bubble-bursting tank experiments were conducted in and around the plankton bloom. 5250 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267

Fig. 9.6. (Top panel) Near surface sea-spray mass concentrations around the European regions and average wind vectors. (Bottom Panel) Percentage primary organic contribution to sea-spray mass.

the North East Atlantic. The model predicted results compare well (MSA). Some dicarboxylic acids were associated with secondary to seasonal observations at Mace Head and are illustrated for winter formation mechanisms in previous papers (i.e. Kawamura and and summer seasons in Fig. 9.6. Sakaguchi, 1999) but a relevant fraction of the observed concentrations of oxidized organic matter in marine aerosol still remains 9.2.3. Secondary aerosol production unaccounted. Modelling studies by Meskhidze and Nenes (2006), In recent years, significant effort has been made into the study of proposed that isoprene emissions from plankton were sufficient new particle formation in the coastal zone in the hope that it would to produce enough water-soluble organic aerosol to significantly elucidate key processes associated with nucleation over the open enhance CCN concentrations and cloud albedo; however, it was ocean. Most of these studies have focused on nucleation in coastal later revealed that the isoprene fluxes were inadvertently over- zones (e.g. at Mace Head) and revealed regular particle bursts, with estimated by a factor of 100. Nevertheless, Zorn et al. (2008) also burst concentrations often exceeding 106 cm3. These events have confirmed the dominance of organic aerosol mass in air overlying been linked to release of biogenic iodine vapours from coastal algae plankton blooms over the southern ocean but no detail on speci- followed by the photochemical production of iodine oxide aerosols ation was elucidated. Recently a new secondary organic aerosol (O’Dowd et al., 2002; McFiggans et al., 2004). A detailed review of component, produced through the reaction of gaseous amines with studies into these processes is found in O’Dowd and Hoffmann sulphuric acid has been found in marine aerosol over the North (2005). Further studies revealed that the nucleation mode particles Atlantic (Facchini et al., 2008). Dimethyl and diethyl ammonium could also contain some organic aerosol mass suggesting that salts (DMAþ and DEAþ) are the most abundant organic species, secondary organic aerosol production also occurs in marine air second only to MSA, detected in fine marine particles in North and contributes to aerosol growth (Vaattovaara et al., 2006). The Atlantic and represent on average 11% of SOA and a dominant part findings of O’Dowd et al. (2004) and Ceburnis et al. (2008) also (35% on average) of the aerosol water-soluble organic nitrogen point to significant contributions of secondary organic aerosol, (WSON). Several evidences support the hypothesis that DMAþ and manifesting itself in the WSOC component. The most relevant DEAþ have a biogenic oceanic source even if the formation mech- organic secondary component (SOA) is methanesulphonic acid anism of these biogenic amines remains unclear. D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5251

In conclusion, apart from MSA and a few dicarboxylic acids and which can involve atmospheric organic compounds and oxidants amine salts, the vast majority of secondary organic marine aerosol (airborne microorganisms) (Ariya and Amyot, 2004; Sun and Ariya, remains to be identified, suggesting that other formation mecha- 2006). They also comprise either biological particles including alive, nisms and alternative SOA components should be studied. dead cells and cell fragments, capable of nucleating cloud droplets and ice particles via physical processes (Mo¨hler et al., 2007)oranykindof 10. The processes of wet scavenging of aerosols organic substances deriving from biomolecules and contributing to and trace gases from the atmosphere aerosol masses. Airborne microorganisms are incorporated into cloud droplets and raindrops by nucleation scavenging as they have CCN or 10.1. Introduction IN potential (e.g. Bauer et al., 2003; Mo¨hler et al., 2007)orbywashout processes. Some investigations clearly show that most of these Precipitation or wet scavenging is an efficient cleaning mecha- microorganisms are able to develop at low temperatures (between 5 nism of the atmosphere. It combines all the in and below cloud and 5 C) encountered in clouds. Furthermore, measurements of processes that take up trace gases and particles into liquid drops or concentrations of adenosine triphosphate (ATP) in cloud water indi- crystals forming a cloud and deposits the material to terrestrial or cate that most microorganisms are still metabolically active (Amato marine surfaces in rain or snow. et al., 2007a,b,c,d). Despite the presence of ice in many cloud systems, interactions 10.2. Nucleation scavenging of drops and ice crystals between trace chemicals and ice are not well understood (Abbatt, 2003). Chemical solutes originally dissolved in a supercooled Droplets form on a subset of the aerosol particles, the cloud drop may be retained or expelled from the drop as it freezes. Non- condensation nuclei (CCN), present in every air mass. This mech- volatile species, such as sulphate, are efficiently retained during anism is probably the most important to incorporate pollutants freezing but this retention process is not well characterized for into the cloud phase. Depending on their size, chemical composi- many soluble gases found in clouds (Voisin et al., 2000). Cloud tion and the ambient relative humidity, aerosol particles take up modelling studies have found that partitioning of solutes during a certain amount of water (Pruppacher and Klett, 1997) and when hydrometeor freezing may significantly affect chemical distribu- exceeding their critical size they activate to cloud droplets. In tions in the troposphere and deposition to the ground (Audiffren the classical Ko¨hler theory, only their composition with respect to et al., 1999; Mari et al., 2000; Crutzen and Lawrence, 2000; Yin insoluble material and inorganic salts is considered. Recent studies et al., 2005; Ka¨rcher and Basko, 2004). A better understanding of (e.g. Anttila and Kerminen, 2002; Sorjamaa et al., 2004; Romak- the partitioning of volatile chemical solutes during freezing is kaniemi et al., 2005; Kokkola et al., 2006; Topping et al., 2007)have needed to quantify their effects on tropospheric gas-phase and highlighted the importance of soluble trace gases and partly soluble precipitation chemistry. organic substances which often coat the surface of the particles for Bacteria which have entered the liquid phase find therein the activation properties. a solution of organic compounds which may serve as nutrients. Even though our knowledge of the formation of droplets is now Recent studies show that living and active microorganisms, reasonably satisfactory, the nucleation of ice crystals as a subject is still including bacteria, yeasts and fungi, are present in the atmospheric quite poorly understood. In the atmosphere, significant numbers of ice water phase (Fuzzi et al., 1997; Bauer et al., 2003; Amato et al., 2005, particles start to form only below 5 C co-existing still with liquid 2007a). These microorganisms could play an active role in chemistry drops. Homogeneous freezing of liquid droplets depends on the size; and microphysics of clouds as discussed by a growing number of large droplets can freeze homogeneously at temperatures of around scientists (Ariya and Amyot, 2004; Amato et al., 2005, 2007b; Mo¨hler 33 C, whereas at 40 C even the smallest droplets freeze homo- et al., 2007; Deguillaume et al., 2008). Indeed, living microorganisms geneously. New insight into the homogeneous nucleation of ice crystals are clearly biocatalysts which could transform organic compounds under these conditions which correspond to cirrus clouds was as an alternative route to photochemistry. Many unresolved ques- obtained in the AIDA chamber (Benz et al., 2005; Mo¨hler et al., 2006). In tions remain on this topic and long-term observations can be used the temperature range between 5and40 C,thepresenceof to evaluate the diurnal and seasonal variations of structure and insoluble nuclei is necessary to initiate the formation of an ice crystal. activity of microorganisms as a function of environmental conditions These ice nuclei (IN) are aerosol particles that can act in four mainways: (i.e. humidity, light, temperature, pH.).

– Deposition mode: water is adsorbed directly from the vapour 10.3. Impaction scavenging of aerosol particles phase onto the surface of an IN where it is transformed into ice – Condensation–freezing mode: this is a hybrid process that Inside the cloud unactivated aerosol particles remain between requires supersaturation with respect to water. Here, the CCN the nucleated drops as interstitial aerosol. These particles can that has formed the drop acts now as an IN. This process seems collide with the hydrometeors and become incorporated into the far more effective than the deposition mode. cloud particles. However, due to the fact that already the main part – Freezing mode: the IN, scavenged by the drop, initiates the ice of the particle mass was scavenged by nucleation, inside cloud phase from within a supercooled water droplet this process does not contribute signiﬁcantly to the pollution mass – Contact mode: the IN initiates the ice phase at the moment of in precipitation (Flossmann, 1998a,b; Flossmann and Wobrock, contact with the supercooled drop 1996). An importance can be attributed to this process in combination with the contact mode freezing of the previous section. The number of IN depends on the chemical properties of the Once the hydrometeors fall and leave cloud base, on their way to aerosol particles. It has been found that there exists a dependency the earth’s surface they meet an unperturbed aerosol particles on supersaturation and also on temperature. In contrast to CCN, population. Here, the collision with aerosol particles can contribute a good IN should be insoluble and have a crystalline-type structure a signiﬁcant portion to the aerosol particle loading of the rain on to facilitate the formation of the ice lattice (e.g. silicate). the ground, depending also on the height of cloud base. Recently, the role of primary biological aerosols for nucleation of During the cloud lifetime, chemical processes lead to the drops and ice crystals has been highlighted (Deguillaume et al., 2008). formation of new chemical species with relatively low volatility These particles can be viable organisms capable of metabolic reactions such as inorganic and organic acids, which can modify the physico- 5252 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 chemical properties of aerosol particles after the cloud dissipates (Feingold and Kreidenweis, 2002; Yin et al., 2005) and lead to secondary organic aerosols formation. For some chemical species, aerosol particle dissolution is the only source in cloud droplets; for instance, transition metal ions, and in particular iron, which is well known to play a major role in the oxidizing capacity of clouds (Deguillaume et al., 2005). Study of such complex interactions needs process modelling efforts integrating in situ measurements.

10.4. Scavenging of gases

In addition to the particles, numerous trace gases are present in the atmosphere. Gases are taken up into drops according to their solubility. The maximum amount of a gas that can be taken up into water is a function of the Henry’s law coefficient. A Fig. 10.1. Schematic of the microphysical and scavenging processes in liquid phase comprehensive compilation of updated Henry’s law coefficients is clouds. available at http://www2.mpch-mainz.mpg.de/~sander/res/henry. html. Henry’s law describes the equilibrium between the then transport them over larger distances, processing the material concentration in the air and the liquid, however, once in the liquid during transport. phase most gases are destroyed by chemical reactions and, thus, The problem of correctly describing this process is coupled to the an equilibrium will never be achieved. Consequently, more and problem of scales. As shown below, the nucleation of hydrometeors more gas can be taken up into the cloud drops. Only the droplet and all subsequent reactions take place on the scale of the individual lifetime (max. 30 min) will limit the gas scavenging. Recently, our drop or ice crystal. The formation, transport and dissipation mech- knowledge of the uptake and reaction coefficients of the ambient anisms of clouds, however, act over a much larger region and require trace gases has significantly increased and quite complex aqueous description on a synoptic or even hemispheric scale. In the past, phase reaction schemes have become available (Herrmann et al., this fact imposed severe constraints in the accuracy of the modelling 2005), including an extended reaction mechanism for atmo- of these processes and resulted either in highly parameterised spherically important hydrocarbons containing more than two dynamical models with detailed treatments of the chemistry (Wolke and up to six carbon atoms. et al., 2005; Sander et al., 2005) or in highly simplified chemical The complexities of the cloud processes involved in pollutant schemes in sophisticated meteorological models (Mari et al., 2000). scavenging have discouraged investigators from simultaneously Only recently have 3-D dynamic codes with detailed microphysical treating all aspects of multiphase chemistry and microphysics with treatment and aerosol particles (Leroy et al., 2008) and chemistry equal rigor. However, efforts made to develop sophisticated cloud (Tost et al., 2007) become available due to developments in models with complex multiphase chemistry allow more detailed computers. These models obviously are restricted to rather limited studies on the interaction between microphysical and chemical modelling domains, however, they highlight e.g. the importance of multiphase processes (Leriche et al., 2007; Ervens et al., 2004a,b). the background aerosol population for the development of the cloud One important feature lies in a detailed representation of the (Leroy et al., 2008). microphysical as well as multiphase chemical processes. These Fig. 10.2 displays the results of a sensitivity test for the CRYSTAL- developments really distance themselves from the other attempts FACE cloud (Leroy et al., 2008). The simulation shows a clean of coupling multiphase chemistry in 3D models, which are often boundary layer in which rain develops readily while precipitation restricted to the study of inorganic species and basic organic species formation is suppressed in the polluted case by the large population wet deposition (Tost et al., 2007). of aerosols derived from air pollutants. Not only has the precipitation been suppressed but the horizontal and vertical structure of the 10.5. Clouds cloud is substantially modified. By including as many as possible of these processes in larger Clouds form when air ascends and following expansion and scale models parameterisations have been developed to yield the cooling the water vapour condenses. The droplets grow further by first reliable maps on critical loads (e.g. Hoose et al., 2008; Pozzoli condensation, then, collide and coalesce with each other, until they et al., 2008). One emphasis of these models has been the aspect of become sufficiently heavy to fall against the updraft velocity that topography. has suspended them until now. Depending on the height of cloud base and the temperature conditions they might reach the ground 10.6. Orographic precipitation as rain. If the temperature in the clouds reaches temperatures sufficiently below zero, then ice crystals develop. They also grow by At mid-latitudes, mountainous terrain is commonly associated water vapour deposition, and collide with each other. If they with high annual precipitation due to the forced ascent of air become sufficiently heavy, they fall to the ground in solid or liquid resulting in cloud formation and precipitation. At a sub-grid scale, form, as a function of the below-cloud temperature. During their however, there can be significant variations in pollutant deposition entire lifetime, these cloud hydrometeors (¼drops or ice particles) due to local emissions and variation in topography and vegetation. take up pollution in particulate and gaseous form and deposit it on A need, therefore, arises for fine scale process models to investigate the ground together with precipitation. A schematic display for pollutant deposition at the kilometer scale (Dore et al., 2006). liquid clouds is shown in Fig. 10.1. The aerosol population (size distribution and composition) has Only few clouds form locally due to convection and, thus, have a major influence on the dynamics and microphysics of orographic only a limited geographical impact. Most clouds are embedded in cloud development. The cloud condensation nuclei (CCN) population large-scale system and cover areas of several thousand km2. They entering cloud base determines the extent and onset of warm rain incorporate the local pollution when the droplets nucleate and produced by collision coalescence. These, along with the presence of D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5253

Fig. 10.2. Sensitivity study concerning the number concentration of boundary layer aerosol particles (Leroy et al., 2008) after 40 min of cloud development; the displayed domain is a 2-D cross section of the 3-D domain restricted to 30 km in the horizontal and 15 km in the vertical; the envelopes of the different hydrometeors are specified for each panel. heterogeneous ice nuclei affect the onset of the glaciation process and chemistry have highlighted our lack of knowledge of the organic the efficiency of secondary ice processes such as the Hallett–Mossop nitrogen constituents (both gaseous and particulate) in the process of ice splintering. These in turn determine the release of latent atmosphere. Recent reviews (Cornell et al., 2003; Neff et al., 2002) heat of fusion in the cloud, which has a major influence on the vigour have indicated that the contribution of water soluble organic and structure of the cloud dynamics. The initiation and development nitrogen (WSON) in precipitation to wet deposition may be up to of the ice phase is crucial to the precipitation formation and its loca- one-third of the total, yet little is known about the chemical tion within the cloud. More detailed process studies are needed to composition, form or sources of this material. Initial scepticism understand such complex feedbacks. In the case of orographic clouds, about the nature of WSON has to some extent been dispelled it is shown that aerosol–cloud interactions may cause a displacement (Cape et al., 2001), but the broad range of possible composition of precipitation from the upslope side of a hill towards the downslope and emission sources means that the transfer pathways are still side when the number of aerosols is increased (Muhlbauer and Loh- somewhat uncertain. It is known, for example, that biological mann, 2008). Inverse relations between air pollution and orographic processes interconvert inorganic and organic nitrogen in forest precipitation could be of major interest for weather prediction and canopies (Fang et al., 2008), but it is not clear how much biological hydrological budget evaluation. activity may occur in the atmosphere or on the surfaces of The initial physical and chemical state of aerosol entering the sampling equipment. The presence of both gaseous and particulate clouds is strongly influenced by the prevailing oxidant climate and WSON in the atmosphere implies that dry deposition is an air mass history. The degree of in-particle oxidation and resultant important but unquantified pathway for transfer of organic hygroscopic properties has been seen previously to be closely tied to nitrogen to the earth’s surface. the degree of gas phase photochemical ageing (Cubison et al., 2006). The specificity, in terms of time since surface emission and oxidative exposure, which can be made from direct aerosol measurements, is 10.8. Conclusions and some priority areas of future research however relatively poor. This may be inferred much more accurately however by making coincident measurements of gas phase volatile The processing of atmospheric contaminants as gases and organic tracers (VOCs). particles by clouds and precipitation form part of the biogeochemical cycling within the atmosphere. The gases and particles 10.7. Organic N in air and rain are taken up into cloud hydrometeors during the lifetime of a cloud, processed and either released during evaporation or deposited onto Better understanding of the processes that link the chemical the ground with the liquid or solid precipitation. Knowledge of the and biological properties of aerosols with cloud formation and underlying processes has greatly advanced concerning the liquid droplet growth has indicated a need for better knowledge of the phase. Here, the gap concerning the role of the organic material is organic components. Although transport or organic C, and depo- now almost closed. The greatest uncertainty nowadays lies with the sition to the earth’s surface, has not been regarded as quantita- ice phase. Generally, the ice phase is chemically less active than tively important for ecosystem health, organic N has the potential the liquid phase. Thus, the uptake and processing is reduced. to add to the known effects of inorganic N wet deposited from the Furthermore, the role of the ice phase in the precipitation forma- atmosphere especially in remote areas. Studies of precipitation tion and deposition is not completely known and these weaknesses 5254 D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 in understanding give rise to large uncertainty in values are interactions of the different components are not yet studied mainly obtained by current models. because of instrument and resource limitations. In the 1950s the The second challenge in the modelling of wet deposition is work started with single component fluxes to a few ecosystems. linked to role that bacteria and other living organic matter (bio- Currently, as presented in this section, the state of knowledge is aerosols) can play in the microphysics of a cloud and in atmospheric grouped into families of components (VOC, reactive nitrogen, GHG, aqueous phase chemistry, which is largely unknown. particles), in which our understanding provides regional budgets as well as deposition fluxes of chemical species of interest for 11. Ecosystem–atmosphere exchange – concluding remarks effects assessment and forms a part of continental scale integrated assessment. Clearly, progress has been rapid in some areas, moti- This paper has reviewed the state of knowledge of atmosphere– vated by pressure for control measures. The next steps in the wider surface interactions of a broad range of trace gases and particles. integration will require similar pressure to deliver the necessary Given the wide range of chemical species reviewed and the information to support policy development. reasonably self contained sections within the paper, this concluding Within the area of reactive nitrogen it has been shown that there is section does not attempt to provide a summary of the sections. The a dynamic exchange between the atmosphere and surface, regulated following commentary reflects on the overall direction of the by stomatal and chemical interactions; deposition, re-emission and science which, like the subject material, is becoming ever more re-deposition processes and by the exchange of different forms of global and searching for integrating mechanisms. There has been nitrogen in interaction with the status of the system (saturation, substantial progress over the last decade in process understanding, carbon, phosphorus, water-filled pore space, etc) (Sutton et al., 2008a; field measurement and in modelling. Models have been developed Pilegaard et al., 1995). Sulphur has a large impact on the uptake and incorporating the process understanding to generalize the release of ammonia at the surface. This is all is part of the nitrogen ecosystem–atmosphere exchange over regions and are currently cascade, where one molecule of reactive nitrogen that enters a system able to describe the fluxes with uncertainties of the order of 30% in in oxidized or reduced state is used and transformed in that system, wet deposition and 50% in dry deposition for the main chemical can be leached to the groundwater as nitrate, entering the river and in species. However, there is a lack of measurements to evaluate the the estuaries where it can be emitted as N2O contributing to climate models. For the future, extensive measuring campaigns and long- change and into the stratosphere, where eventually it is broken down term monitoring of fluxes are necessary to further develop this depleting the ozone layer (Galloway et al., 2003). There is evidence important field. The development of super sites in the European that increased nitrogen deposition leads to NO emissions from the soil. EMEP network with a full spectrum of gas and aerosol phase trace This links nitrogen deposition with the oxidant surface–atmosphere atmospheric constituents and continuous measurements of exchange. Oxidants in their turn affect the ecosystem health and surface–atmospheric fluxes represents an important development therewith the nitrogen uptake and use efficiency. These are examples in this direction. The development of long-term micrometeorolog- of the strong interaction between the components in the surface– ical CO2 flux monitoring sites, initially within CarboEurope and atmosphere exchange. followed by AmeriFlux, but now extending to a global network provides much of the infrastructure for extension to trace gases. 11.3. Future developments Such long-term flux measurements of reactive pollutants to test, develop and validate models represent an important development, Agriculture is a major source of emissions to the atmosphere, which, in turn will be expanded regionally. which relative to industry has been regulated substantially less (Aneja et al., 2008). Until now the policy requirements for food security from 11.1. Policy needs agriculture has moderated the willingness to limit emissions of trace gases from this sector. More and more, however, it is recognised that In the policy development there is a need to address environ- the production should be within the limits of sustainability, limiting mental priority issues, among which none are currently greater than pollutant emissions to surface or groundwater and to the atmosphere climate change. However, human health, ecosystem quality and the of reactive nitrogen compounds, greenhouse gases, persistent organic sustainable use of natural resources is growing in importance. pollutants, phosphorus and odour. Agriculture is a collection of diffuse There is a current tendency to group the environmental impacts sources with many uncertainties in the emissions. Greenhouse gas because they are linked through the pollutants and the receptor emissions and ammonia are uncertain because the emissions depend which follows historical tradition. New, much broader and more on farm management practices, soil type, fertilizer use, type of crop integrated directions include global change, reactive nitrogen, or animal breeding, size and location of the farm, etc. This makes air quality and climate change, bringing together a range of related quantification of the sources and successful targeted measures and issues in the search for more sustainable solutions to the under- policies for control very difficult. lying problems. This is however far from being implemented in The next step will include quantifying the strong interactions policies because it involves a larger scale and therewith global between land use, food supply, biodiversity and biogeochemical political developments. However, the process has begun within cycling of key nutrients. Studying these landscape interactions is initiatives such as those described in the Millenium Ecosystem a new topic, where just a few exercises have been attempted. The Assessment (2005). Ultimately, political developments will be landscape scale, such as agricultural areas, complex terrain, urban required to allow such integrated environmental policies to be areas, etc. have their own dynamic and interactions which differ developed, but evidence of the time it is taking to develop appro- from the normally studied stationary conditions. It is necessary to priate controls to limit greenhouse gas emissions suggest that study this scale because of the need to determine the contribution it will be a slow process. of the individual sources which need to be controlled. In rural, agriculture dominated areas there is a large contribution of 11.2. Current understanding different reactive nitrogen sources, such as animals in- or outside housing systems, application of fertilizers or manure, storage of It is questionable whether our current understanding of the manure, traffic and small industries. Within such an area deposi- atmosphere–surface exchange is keeping pace with these more tion and re-emission takes place with a high spatial and temporal integrated needs. The processes are very variable and the dynamic. Especially for nitrogen the efficiency of use can be D. Fowler et al. / Atmospheric Environment 43 (2009) 5193–5267 5255 improved if the individual contribution of the different sources and Doˆme: major groups and growth abilities at low temperatures. FEMS Micro- resulting losses can be quantified. biology Ecology 59 (2), 242–254. Amato, P., Hennebelle, R., Magand, O., Sancelme, M., Delort, A.-M., Barbante, C., The majority of surface–atmosphere exchange measurements Boutron, C., Ferrari, C., 2007b. Bacterial characterization of the snow cover at have been made in rural landscapes, yet a large fraction of emissions Spitzberg, Svalbard. FEMS Microbiology Ecology 59 (2), 255–264. occur in urban areas, where most of the global human population Amato, P., Demeer, F., Melaouhi, A., Martin-Biesse, A.-S., Sancelme, M., Laj, P., Delort, A.-M., 2007c. A fate for organic acids, formaldehyde and methanol in now resides. In urban areas there is a concentration of sources cloud water: their biotransformation by micro-organisms. Atmospheric of gases and pollutants from industry, traffic and households. The Chemistry and Physics 7, 4159–4169. emissions to the atmosphere and the resulting exposure in these Amato, P., Parazols, M., Sancelme, M., Mailhot, G., Laj, P., Delort, A.-M., 2007d. An important oceanic source of micro-organisms for cloud water at the puy de areas are therefore a growing concern globally and our knowledge Dˆ ome (France). Atmospheric Environment 41, 8253–8263. base for many of the processes in these areas is very limited. This Ammann, C., Brunner, A., Spirig, C., Neftel, A., 2006. 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