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Agriculture is the main source of ammonia (NH3) in France, an important gaseous precursor of atmospheric particulate matter (PM). National and global emission inventories are known to have difficulty representing the large spatial and temporal variability inherent to atmospheric NH3. In this study, we compare NH3 emissions in France during spring 2011 from one reference inventory, the TNO inventory, and two alternative inventories that account in different manners for both the spatial and temporal variabilities of the emissions: (i) the NH3SAT satellite-derived inventory based on IASI NH3 columns and (ii) the CADASTRE-CIT inventory that combines NH3 emissions due to nitrogen fertilization calculated with the mechanistic model VOLT'AIR on the database of the CADASTRE_NH3 framework and other source emissions from the CITEPA. The total spring budgets, from March to May 2011, at the national level are higher when calculated with both alternative inventories than with the reference, the difference being more marked with CADASTRE-CIT. NH3SAT and CADASTRE-CIT inventories both yield to large NH3 spring emissions due to fertilization on soils with high pH in the northeastern part of France (65 and 135 kt NH3, respectively, vs. 48 kt NH3 for TNO-GEN), while soil properties are not accounted for by the TNO-GEN methodology. For the other parts of France, the differences are smaller. The timing of fertilization and associated ammonia emissions is closely related to the nitrogen requirements and hence the phenological stage of the crops, and therefore to the crop year's specific weather conditions. Maximum emissions are observed in March for 2011 for some regions for both alternative inventories, while April is the period with maximum emissions for the reference inventory regardless of the region or the year. Comparing the inventories at finer temporal resolutions, typically at daily scale, large differences are found. The convergence of alternative, independent and complementary methods on the spatiotemporal representation of the spring NH3 emissions, particularly over areas where the contribution of mineral fertilizer spreading to the spring budget is strong, encourages further developments in both prospective complementary directions, as this will help improve national NH3 emission inventories.

Tropospheric ammonia (NH3) is a threat to the environment and human health and is mainly emitted by agriculture. Ammonia volatilisation following application of nitrogen in the field accounts for more than 40 % of the total NH3 emissions in France. This represents a major loss of nitrogen use efficiency which needs to be reduced by appropriate agricultural practices. In this study we evaluate a novel method to infer NH3 volatilisation from small agronomic plots consisting of multiple treatments with repetition. The method is based on the combination of a set of NH3 diffusion sensors exposed for durations of 3 h to 1 week and a short-range atmospheric dispersion model, used to retrieve the emissions from each plot. The method is evaluated by mimicking NH3 emissions from an ensemble of nine plots with a resistance analogue–compensation point–surface exchange scheme over a yearly meteorological database separated into 28-day periods. A multifactorial simulation scheme is used to test the effects of sensor numbers and heights, plot dimensions, source strengths, and background concentrations on the quality of the inference method. We further demonstrate by theoretical considerations in the case of an isolated plot that inferring emissions with diffusion sensors integrating over daily periods will always lead to underestimations due to correlations between emissions and atmospheric transfer. We evaluated these underestimations as −8 % ± 6 % of the emissions for a typical western European climate. For multiple plots, we find that this method would lead to median underestimations of −16 % with an interquartile [−8–22 %] for two treatments differing by a factor of up to 20 and a control treatment with no emissions. We further evaluate the methodology for varying background concentrations and NH3 emissions patterns and demonstrate the low sensitivity of the method to these factors. The method was also tested in a real case and proved to provide sound evaluations of NH3 losses from surface applied and incorporated slurry. We hence showed that this novel method should be robust and suitable for estimating NH3 emissions from agronomic plots. We believe that the method could be further improved by using Bayesian inference and inferring surface concentrations rather than surface fluxes. Validating against controlled source is also a remaining challenge.

Ammonia concentration and fluxes were measured above a growing triticale field for two months during May and June 2010 at the NitroEurope crop site in Grignon (Fr-Gri) near Paris, France. The measurement campaign started 15 days following a 40 kg N ha−1 application of an ammonium nitrate solution. A new mini-wedd (Wet Effluent Denuder) flow injection analyser with three channels (ROSAA, RObust and Sensitive Ammonia Analyser) was used to measure NH3 fluxes using the aerodynamic gradient method. The measured ammonia concentrations varied from 0.01 to 39 μg NH3 m−3 and were largely influenced by advection from the nearby farm. The ammonia fluxes ranged from –560 to 220 ng NH3 m−2 s−1 and averaged –29 ng NH3 m−2 s−1. During some periods the large deposition fluxes could only be explained by a very small surface resistance, which may be partly due to the high concentrations of certain acid gases (HNO3 and SO2) observed in this suburban area. Ammonia emissions were also observed. The canopy compensation point Cc was around 1.5 μg NH3 m−3 on average. The canopy emission potential Γc (Cc normalised for the temperature response of the Henry equilibrium) decreased over the course of the measurement campaign from Γc = 2200 to Γc = 450, the latter value being close to the median stomatal emission potential (Γs) and lower than the median ground emission potential (Γg) for managed ecosystems reported in the literature. The temporal dynamics of the measured NH3 flux compared well with the Surfatm-NH3 model using fitted parameters. The subjectivity of the model fitting is discussed based on a sensitivity analysis.

Accurate estimations of ammonia (NH 3 ) emissions due to nitrogen (N) fertilization are required to identify efficient mitigation techniques and improve agricultural practices. Process-based models such as Volt'Air can be used for this purpose because they incorporate the effects of several key factors influencing NH 3 volatilization at fine spatio-temporal resolutions. However, these models require a large number of input variables and their implementation on a large scale requires long computation times that may restrict their use by public environmental agencies. In this study, we assess the capabilities of various types of meta-models to emulate the complex process-based Volt'Air for estimating NH 3 emission rates from N fertilizer and manure applications. Meta-models were developed for three types of fertilizer (N solution, cattle farmyard manure, and pig slurry) for four major agricultural French regions (Bretagne, Champagne-Ardenne, Ile-de-France, and Rhône-Alpes) and at the national (France) scale. The meta-models were developed from 106,092 NH 3 emissions simulated by Volt'Air in France. Their performances were evaluated by cross-validation, and the meta-models providing the best approximation of the original model were selected. The results showed that random forest and ordinary linear regression models were more accurate than generalized additive models, partial least squares regressions, and least absolute shrinkage and selection operator regressions. Better approximations of Volt'Air simulations were obtained for cattle farmyard manure (3% < relative root mean square error of prediction (RRMSEP) < 8%) than for pig slurry (17% < RRMSEP < 19%) and N solution (21% < RRMSEP < 40%). The selected meta-models included between 6 and 15 input variables related to weather conditions, soil properties and cultural practices. Because of their simplicity and their short computation time, our meta-models offer a promising alternative to process-based models for NH 3 emission inventories at both regional and national scales. Our approach could be implemented to emulate other process-based models in other countries., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

In France, agriculture is responsible for 98% of ammonia (NH 3 ) emissions with over 50% caused by nitrogen (N) fertilization. The current French national inventory is based on default emission factors (EF) and does not account for the main variables influencing NH 3 emissions. To model the spatio-temporal variability of NH 3 emissions due to mineral and organic N fertilization, we implemented a new method named CADASTRE&#95;NH 3 . The novelty lies in the combined use of two types of resources: the process-based Volt'Air model and geo-referenced and temporally explicit databases for soil properties, meteorological conditions and N fertilization. Simulation units are the Small Agricultural Regions. Several sources of information were combined to obtain N fertilization management: census and surveys of the French Ministry of Agriculture, statistics on commercial fertilizer deliveries, and French expertise on physicochemical properties of organic manure. The practical interest of this new framework was illustrated for France during the crop year 2005/06. Aggregation at crop year level showed a reasonable agreement between estimated values derived from CADASTRE&#95;NH 3 and those from the French inventory method, for N and ammoniacal-N (TAN) application rates, total NH 3 emissions and NH 3 EF. Discrepancies were large for organic manure only; national TAN application rates and NH 3 emissions were 62-63% lower with CADASTRE&#95;NH 3 . This was due to divergences in the representation of cattle farm yard manure and in the TAN:N ratio of solid manure. Annual emissions for fertilization in France were estimated to be 270 Gg NH 3 , 29% lower than the French national inventory estimate. At the regional level, organic manure contributed to 73% of field NH 3 emissions in intensive livestock husbandry areas and to 41% in the other areas. The CADASTRE&#95;NH 3 framework can be seen as a Tier 3 approach able to estimate specific regional EF for different mineral fertilizers and organic manure., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The data presented in this article are related to the research article entitled "A new framework to estimate spatio-temporal ammonia emissions due to Nitrogen fertilization in France" (Ramanantenasoa et al., 2018) but are given with more details at a regional scale (NUTS2) in the objective to get them available for other research or applied studies. They concerns (i) the data implemented in the CADASTRE&#95;NH 3 framework and (ii) the data obtained using it, for crop year 2005/06. For the source data, the article focusses on the N fertilization practice management description, as this dataset is the most difficult to collect and to analyze in the objective of realistically representing the spatial and temporal variabilities needed in the framework.

Pesticide volatilization from bare soil exhibits usually a diurnal cycle with a potentially large decrease when the soil surface dries. We assume here that this decrease may be due to the increase in adsorption of gaseous pesticides to soil under dry conditions. Thus, a precise description of the change with time of water content of the soil surface and of additional process such as gaseous adsorption is required. We used the Volt'Air model: we first extended the van Genuchten curve to drier conditions and then inserted a partitioning coefficient of the pesticide between the air-filled pore space and the soil constituents. This coefficient was calculated by a quantum-chemistry-based method with a dependence on the Specific Surface Area of the soil (SSA) and Relative Humidity (RH) of the air-filled pore space. These developments were assessed by comparing with two data sets on volatilization of trifluralin applied to bare soil. The updated Volt'Air model allowed a better description of the volatilization dynamics on a diurnal cycle (increasing efficiency factor from 0.85 to 0.96 and -2.73 to 0.17 and decreasing RMSE from 146 to 78 and 353 to 168 for both scenarios) as well as the effect of a rewetting situation. Recommendations are made for further refining the description of this process together with the soil water conditions.

Ammonia and pesticide volatilization in the field is a surface phenomenon involving physical and chemical processes that depend on the soil surface temperature and water content. The water transfer, heat transfer and energy budget sub models of volatilization models are adapted from the most commonly accepted formalisms and parameterizations. They are less detailed than the dedicated models describing water and heat transfers and surface status. The aim of this work was to assess the ability of one of the available mechanistic volatilization models, Volt'Air, to accurately describe the pedo-climatic conditions of a soil surface at the required time and space resolution. The assessment involves: (i) a sensitivity analysis, (ii) an evaluation of Volt'Air outputs in the light of outputs from a reference Soil-Vegetation-Atmosphere Transfer model (SiSPAT) and three experimental datasets, and (iii) the study of three tests based on modifications of SiSPAT to establish the potential impact of the simplifying assumptions used in Volt'Air. The analysis confirmed that a 5 mm surface layer was well suited, and that Volt'Air surface temperature correlated well with the experimental measurements as well as with SiSPAT outputs. In terms of liquid water transfers, Volt'Air was overall consistent with SiSPAT, with discrepancies only during major rainfall events and dry weather conditions. The tests enabled us to identify the main source of the discrepancies between Volt'Air and SiSPAT: the lack of gaseous water transfer description in Volt'Air. They also helped to explain why neither Volt'Air nor SiSPAT was able to represent lower values of surface water content: current classical water retention and hydraulic conductivity models are not yet adapted to cases of very dry conditions. Given the outcomes of this study, we discuss to what extent the volatilization models can be improved and the questions they pose for current research in water transfer modeling and parameterization., (Copyright © 2011 Elsevier B.V. All rights reserved.)

A need exists to improve the utilization of manure nutrients by minimizing NH(3) emissions from land application of manure. Management strategies to reduce NH(3) emissions are available; however, few have been validated under Canadian conditions. A well tested and accurate simulation model, however, can help overcome this challenge by determining appropriate management strategies for a given set of field conditions. The Volt'Air simulation model was utilized to estimate NH(3) volatilization from manure spreading for various manure spreading considerations under a range of atmospheric conditions typically encountered in eastern Canada. Considerations included: (i) soil liming, (ii) time of day of manure spreading, (iii) rainfall (timing and amount) and (iv) manure incorporation (timing, depth and manure coverage). Results demonstrated that liming to increase soil pH, increased NH(3) emissions by 3.3 kg ha(-1) for each increment of 0.1 pH (up to a 1.5 total increase), over no liming at 34.6 kg ha(-1). For each hour delay in manure spreading past 0800 h, NH(3) losses were reduced by 1.5 kg ha(-1). Rainfall (10mm) at least 20 h after manure application reduced losses, with increased reductions at higher rainfall amounts. Incorporation soon (1h) after application was best for NH(3) mitigation. Increasing the depth of incorporation by 5c m reduced NH(3) emissions by 4.4 kg ha(-1); also increasing manure coverage by incorporation reduced losses by 2 kg ha(-1) for each 10% increase in coverage, compared to surface application at 34.6 kg ha(-1). This investigation using Volt'Air yielded valuable information about simulating manure management strategies and the magnitude of their effects on NH(3) emissions.

The aims of this study were to (i) assess N fluxes (mineralization, volatilization, denitrification, leaching) caused by spreading various organic wastes from food-processing industries during a field experiment, and (ii) to identify the main factors affecting N transformation processes after field spreading. Experimental treatments including the spreading of six types of waste and a control soil were set up in August 2000 and studied for 22 mo under bare soil conditions. Ammonia and nitrous oxide emissions, and nitrogen mineralization were measured in experimental devices and extrapolated to field conditions or computed in calculation models. The ammonia emissions varied from 80 to 580 g kg(-1) NH4+-N applied, representing 0 to 90 g N kg(-1) total N applied. Under these meteorologically favorable conditions (dry and warm weather), waste pH was the main factor affecting volatilization rates. Cumulated N2O-N fluxes were estimated at 2 to 5 g kg(-1) total N applied, which was quite low due to the low soil water content during the experimental period; water-filled pore space (WFPS) was confirmed as the main factor affecting N2O fluxes. Nitrogen mineralization from wastes represented 126 to 723 g N kg(-1) organic N added from the incorporation date to 14 May 2001 and was not related to the organic C to organic N ratio of wastes. Nitrogen lost by leaching during the equivalent period ranged from 30 to 890 g kg(-1) total N applied. The highest values were obtained for wastes having the highest inorganic N content and mineralization rates.