International audienceExisting descriptions of bi-directional ammonia (NH3) land-atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission-deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28-67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100

Abstract. Current deposition schemes used in atmospheric chemical transport models do not generally account for bidirectional exchange of ammonia (NH 3 ). Bi-directional exchange schemes, which have so far been applied at the plot scale, can be included in transport models, but need to be parameterised with appropriate values of the ground layer compensation point (χ g ), stomatal compensation point (χ s ) and cuticular resistance (R w ). We review existing measurements of χ g , χ s as well as R w and compile a comprehensive dataset from which we then propose generalised parameterisations. χ s is related to s , the non-dimensional ratio of [NH + 4 ] apo and [H + ] apo in the apoplast, through the temperature dependence of the combined Henry and dissociation equilibrium. The meta-analysis suggests that the nitrogen (N) input is the main driver of the apoplastic and bulk leaf concentrations of ammonium (NH + 4 apo , NH + 4 bulk ). For managed ecosystems, the main source of N is fertilisation which is reflected in a peak value of χ s a few days following application, but also alters seasonal values of NH + 4 apo and NH + 4 bulk . We propose a parameterisation for χ s which includes peak values as a function of amount and type of fertiliser application which gradually decreases to a background value. The background χ s is based on total N input to the ecosystem as a yearly fertiliser application and N deposition (N dep ). For non-managed ecosystems, χ s is parameterised based solely on the link with N dep .For R w we propose a general parameterisation as a function of atmospheric relative humidity (RH), incorporating a minimum value (R w(min) ), which depends on the ratio of atmospheric acid concentrations (SO 2 , HNO 3 and HCl) toCorrespondence to: R.-S. Massad (massad@grignon.inra.fr) NH 3 concentrations. The parameterisations are based mainly on datasets from temperate locations in northern Europe making them most suitable for up-scaling in these regions (EMEP model for example). In principle, the parameterisations should be applicable to other climates, though there is a need for more underpinning data, with the uncertainties being especially large for tropical and subtropical conditions.

Atmospheric ammonia (NH₃) dominates global emissions of total reactive nitrogen (N_r), while emissions from agricultural production systems contribute about two-thirds of global NH₃ emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH₃ emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH₄⁺) to all surfaces. However, the land/atmosphere exchange of gaseous NH₃ is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH₃ emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH₃ emission potentials defined at the substrate and leaf levels by different [NH₄⁺] / [H⁺] ratios (Γ). Surface/atmosphere exchange models for NH₃ are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of airborne and deposited NH₃ and NH₄⁺. Models of soil/vegetation/atmosphere NH₃ exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterization, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations

Abstract. Nitrogen applied to the surface of the land for agricultural purposes represents a significant source of reactive nitrogen (Nr) that can be emitted as a gaseous Nr species, be denitrified to atmospheric nitrogen (N2), run off during rain events or form plant-useable nitrogen in the soil. To investigate the magnitude, temporal variability and spatial heterogeneity of nitrogen pathways on a global scale from sources of animal manure and synthetic fertilizer, we developed a mechanistic parameterization of these pathways within a global terrestrial land model, the Community Land Model (CLM). In this first model version the parameterization emphasizes an explicit climate-dependent approach while using highly simplified representations of agricultural practices, including manure management and fertilizer application. The climate-dependent approach explicitly simulates the relationship between meteorological variables and biogeochemical processes to calculate the volatilization of ammonia (NH3), nitrification and runoff of Nr following manure or synthetic fertilizer application. For the year 2000, approximately 125 Tg N yr−1 is applied as manure and 62 Tg N yr−1 is applied as synthetic fertilizer. We estimate the resulting global NH3 emissions are 21 Tg N yr−1 from manure (17 % of manure production) and 12 Tg N yr−1 from fertilizer (19 % of fertilizer application); reactive nitrogen runoff during rain events is calculated as 11 Tg N yr−1 from manure and 5 Tg N yr−1 from fertilizer. The remaining nitrogen from manure (93 Tg N yr−1) and synthetic fertilizer (45 Tg N yr−1) is captured by the canopy or transferred to the soil nitrogen pools. The parameterization was implemented in the CLM from 1850 to 2000 using a transient simulation which predicted that, even though absolute values of all nitrogen pathways are increasing with increased manure and synthetic fertilizer application, partitioning of nitrogen to NH3 emissions from manure is increasing on a percentage basis, from 14 % of nitrogen applied in 1850 (3 Tg NH3 yr−1) to 17 % of nitrogen applied in 2000 (21 Tg NH3 yr−1). Under current manure and synthetic fertilizer application rates we find a global sensitivity of an additional 1 Tg NH3 (approximately 3 % of manure and fertilizer) emitted per year per °C of warming. While the model confirms earlier estimates of nitrogen fluxes made in a range of studies, its key purpose is to provide a theoretical framework that can be employed within a biogeochemical model, that can explicitly respond to climate and that can evolve and improve with further observation.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N O emissions. Yield-scaled N O emissions (N O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N O emissions at field scale is discussed.

C4-type photosynthesis is known to vary with growth and measurement temperatures. In an attempt to quantify its variability with measurement temperature, the photosynthetic parameters -the maximum catalytic rate of the enzyme ribulose 1·5-bisphosphate carboxylase/oxygenase (Rubisco) (Vcmax), the maximum catalytic rate of the enzyme phosphoenolpyruvate carboxylase (PEPC) (Vpmax) and the maximum electron transport rate ( These parameters should be further tested with C4 plants for validation. Other model key parameters such as the mesophyll cell conductance to CO2 (gi), the bundle sheath cells conductance to CO2 (gbs) and Michaelis-Menten constants for CO2 and O2 (Kc, Kp and Ko) also vary with temperature and should be better parameterized.

Biogeochemical simulation models are important tools for describing and quantifying the contribution of agricultural systems to C sequestration and GHG source/sink status. The abundance of simulation tools developed over recent decades, however, creates a difficulty because predictions from different models show large variability. Discrepancies between the conclusions of different modelling studies are often ascribed to differences in the physical and biogeochemical processes incorporated in equations of C and N cycles and their interactions. Here we review the literature to determine the state-of-the-art in modelling agricultural (crop and grassland) systems. In order to carry out this study, we selected the range of biogeochemical models used by the CN-MIP consortium of FACCE-JPI (http://www.faccejpi.com): APSIM, CERES-EGC, DayCent, DNDC, DSSAT, EPIC, PaSim, RothC and STICS. In our analysis, these models were assessed for the quality and comprehensiveness of underlying processes related to pedo-climatic conditions and management practices, but also with respect to time and space of application, and for their accuracy in multiple contexts. Overall, it emerged that there is a possible impact of ill-defined pedo-climatic conditions in the unsatisfactory performance of the models (46.2%), followed by limitations in the algorithms simulating the effects of management practices (33.1%). The multiplicity of scales in both time and space is a fundamental feature, which explains the remaining weaknesses (i.e. 20.7%). Innovative aspects have been identified for future development of C and N models. They include the explicit representation of soil microbial biomass to drive soil organic matter turnover, the effect of N shortage on SOM decomposition, the improvements related to the production and consumption of gases and an adequate simulations of gas transport in soil. On these bases, the assessment of trends and gaps in the modelling approaches currently employed to represent biogeochemical cycles in crop and grassland systems appears an essential step for future research.

Abstract. Nitrogen applied to the surface of the land for agricultural purposes represents a significant source of reactive nitrogen (Nr) that can be emitted as a gaseous Nr species, be denitrified to atmospheric nitrogen (N2), run-off during rain events or form plant useable nitrogen in the soil. To investigate the magnitude, temporal variability and spatial heterogeneity of nitrogen pathways on a global scale from sources of animal manure and synthetic fertilizer, we developed a mechanistic parameterization of these pathways within a global terrestrial model. The parameterization uses a climate dependent approach whereby the relationships between meteorological variables and biogeochemical processes are used to calculate the volatilization of ammonia (NH3), nitrification and run-off of Nr following manure or fertilizer application. For the year 2000, we estimate global NH3 emission and Nr dissolved during rain events from manure at 21 and 11 Tg N yr−1, respectively; for synthetic fertilizer we estimate the NH3 emission and Nr run-off during rain events at 12 and 5 Tg N yr−1, respectively. The parameterization was implemented in the Community Land Model from 1850 to 2000 using a transient simulation which predicted that, even though absolute values of all nitrogen pathways are increasing with increased manure and synthetic fertilizer application, partitioning of nitrogen to NH3 emissions from manure is increasing on a percentage basis, from 14 % of nitrogen applied (3 Tg NH3 yr−1) in 1850 to 18 % of nitrogen applied in 2000 (22 Tg NH3 yr−1). While the model confirms earlier estimates of nitrogen fluxes made in a range of studies, its key purpose is to provide a theoretical framework that can be employed within a biogeochemical model, that can explicitly respond to climate and that can evolve and improve with further observation.