# Measurement and modelling of NO fluxes over maize and wheat crops during their growing seasons: effect of crop management

P. Laville, C. Hénault, B. Gabrielle, Dominique Serça

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P. Laville, C. Hénault, B. Gabrielle, Dominique Serça. Measurement and modelling of NO fluxes over maize and wheat crops during their growing seasons: effect of crop management. Nutrient Cycling in Agroecosystems, 2005, 72 (2), pp.159-171. 10.1007/s10705-005-0510-5. hal-00023220

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# Measurement and modelling of NO fluxes on maize and wheat crops during their growing seasons: effect of crop management

P. Laville¹*, C. Hénault², B. Gabrielle¹ and D. Serça³

¹INRA, Unité Environnement et Grandes Cultures, Thiverval-Grignon, France; ²INRA, UMR INRA-Université de Bourgogne Microbiologie et Géochimie des Sols, Dijon, France; ³Laboratoire d'Aérologie, Université Paul Sabatier, Toulouse, France; *Author for correspondence (UMR INRA INA P-G Environnement et Grandes Cultures, 78850 Thiverval-Grignon, France; e-mail: laville@grignon.inra.fr; fax: +33-1-30-81-55-63)

Key words: Arable soils, Biogenic, Influencing factors, Modelling, NO emission

## Abstract

Fertilized agricultural soils are a significant source of NO, a gas involved in tropospheric ozone formation. The aims of the research reported here were to measure NO fluxes over the length of the growing season of wheat and maize crops, and to build a model of soil NO emissions from arable land. Field experiments were carried out on a 1-ha field divided into two parts. The first one was cropped with wheat and harvested in late July, 2002, whereas the second part was sown with maize and harvested in October. The wheat and maize received 130 kg N ha⁻¹ and 140 kg N ha⁻¹, respectively. For each crop, NO fluxes were measured during 10 months every 2 weeks using manual closed chambers, and continuously with a wind tunnel immediately after nitrogen fertilization. Fertilizer application significantly affected NO emissions: the largest NO emissions were recorded a few days after nitrogen application. This delay depended on the kinetics of nitrogen incorporation in the soil, as influenced by rainfall. The emissions measured on the maize field (2.6% of the fertilizer amount applied) were more important than those on the wheat field (1.0% of the fertilizer amount applied), owing to differences in timing of nitrogen application, with respect to climate and crop growth. Relationships between soil nitrification rate and NO emission obtained from laboratory incubations, and experimental data appeared useful and relevant to predict NO emissions at the field-scale.

## Introduction

Nitrogen oxides (NOₓ = NO + NO₂) play a central role in the tropospheric photochemistry leading to ozone formation. Because of the potential damage of ozone on plants, human health and climate, the emissions of NOₓ are of considerable concern. In terms of global source strength, biogenic emissions from soils are highly uncertain,

with global estimates ranging between 5.5 and 21 Tg N (Yienger and Levy 1995; Davidson 1991), and accounting for up to 40% of the global NOₓ budget (Davidson and Kingerlee 1997). Using an empirical model, Yienger and Levy (1995) identified agricultural soils, grassland and tropical rain forest as the largest sources of soil NOₓ, accounting for 41, 35 and 16% of the global annual soil NOₓ budget, respectively. With
predicted increases in N fertilizer use, the agri-
cultural source of atmospheric NOₓ is likely to
increase and to contribute to more than 50% of
the global soil emissions in the future (Yienger
and Levy 1995).

In arable soils, nitric oxide (NO) is predomini-
nantly produced by nitrification and denitrifica-
tion, both microbial pathways, and through the
chemical decomposition of HNO₂. Nitrification is
the oxidation of NH₄⁺ to NO₃⁻, whereas denitri-
fication is the anaerobic reduction of NO₃⁻ to
gaseous forms of N (Bremner and Blackmer
1978). Nitric oxide is a by-product of the nitrifi-
cation pathway, and the typical yield of NO in
well aerated soil ranges from 1% to 4% of the
NH₄⁺ oxidized (Hutchinson and Brams 1992).
Nitric oxide is also a direct intermediate of the
denitrification pathway, and its net release is
greatly influenced by its gas phase diffusivity in
the soil, and its consumption by denitrifiers.
Under anaerobic conditions, the probability of
NO being consumed by the denitrifying commu-
nity is highly enhanced. Many authors empha-
sized that nitrification seems to be the dominant
process of NO emission for many soils (Bollmann
et al. 1999; Dunfield and Knowles 1999; Godde
and Conrad 2000). Ammonium-based fertilizers
increase NO emissions both by stimulating NO
production by nitrification, and by decreasing
NO consumption.

In general, the magnitude of soil NO production
depends on the rates of nitrification and denitrifi-
cation, and on soil diffusion properties. The most
important regulating factors include soil mineral
nitrogen content, soil temperature, and those soil
variables which control gaseous diffusivity: soil
texture, bulk density, and water content. These
different factors are in turn largely influenced by
agricultural management practices such as tillage
and timing of fertilizer applications.

The large uncertainties in the soil NO source
budget result from the paucity of available mea-
surements encompassing the whole duration of
crops' growing periods, along with the simplified
approaches used to model the processes responsi-
ble for NO production in various ecosystems. On a
global scale, most models are currently based on a
mean emission factor depending on the considered
biome, which results in most cases from inventory
of literature review (Potter et al. 1996; Davidson
and Kingerlee 1997; Davidson et al. 1998; Ludwig

et al. 2001). These emission factors may be linked
to environmental variables such as soil tempera-
ture or humidity (Williams et al. 1992; Yienger and
Levy 1995; Potter et al. 1996; Stohl et al. 1996). In
most cases, NO fluxes are proportional to an
exponential function of the soil temperature, with
the proportionality factor depending on the type
of biome considered. This factor is generally con-
stant, except for arable land where it varies as a
function of nitrogen fertilizer inputs.

When applied to arable land, these kind of
models suffers severe limitations: they do not take
into account climatic context, soil characteristics,
or agricultural management (irrigation and tillage
timings, quantity and form of nitrogen inputs).

The first objective of this paper was to propose a
consistent database of NO fluxes measured on the
field scale during several months under maize and
wheat crop. The second was to relate NO emis-
sions to nitrification rates using laboratory and
field measurements.

**Material and methods**

Site description

Experiments were carried out on a 1-ha field at
Grignon in the Paris (France) area (48.9° N,
1.95° E). The soil was a silt loam, with 33% clay
and 16% sand in the surface, and an alkaline pH
(pH in water of 8.3). Surface organic carbon
content was 21.78 g kg⁻¹, and C/N ratio was 12.6.
In the top 15 cm, soil bulk density was
1.21 g cm⁻³ for the wheat crop, and 1.13 g cm⁻³
for the maize crop.

The field was divided into two parts. One was
sown with wheat on October 10, 2001 and fertil-
ized with 50 kg N ha⁻¹ as UAN solution (50% as
urea + 50% as NH₄NO₃) on March 4 and 80 kg
N ha⁻¹ as NH₄NO₃ granules on April 3, 2002. The
wheat (*Triticum aestivum* L.) was harvested on
July 22, 2002. The second part was sown with
maize (*Zea mays* L.) on April 17, 2002, fertilized
with 140 kg N ha⁻¹ as UAN solution on April 25,
and harvested on October 21.

The major climatic variables (including solar
radiation, air and soil temperature, wind speed, air
and soil humidity, rainfall) were continuously
recorded with a data logger (Campbell Scientific,
CR10, Sherpard UK), during the entire
experiment (October 2001 to October 2002). The data logger and the different sensors were located between the two parts of the field, so that soil temperature and moisture probes could be placed under the two crops using the same data logger. Soil water content was continuously recorded using TDR (Tme Domain Reflectrometry, CS615 Campbell Scientific) in the top 15 cm.

Every 2 weeks, soil samples were taken to measure mineral nitrogen content (NO₃⁻, NH₄⁺). Plant status was also characterized (LAI, dry matter, total nitrogen content) during the entire growing period.

Figure 1 shows the variation of the leaf area index for the two crops.

### NO flux measurements

NO fluxes were measured during 10 months every 2 weeks using 3 manual closed chambers for each fields, and continuously with a wind tunnel (Lockyer 1984) in the 2 months following nitrogen fertilization.

### Manual chamber

The manual chambers were made of stainless steel to avoid all surface interactions with nitrogen oxide gases. The chambers were square with a volume of 82 l, and a ground area of 0.25 m². They were attached to a stainless steel frame inserted in the soil to a depth of 10 cm. The air inside the chambers was mixed using a Teflon fan. Gas analysers and data logging systems (Campbell Scientific CR23) were housed in a nearby mobile laboratory. During each sequence of measurements, air was pumped from the chamber to the gas analysers at a flow rate of 2lmin⁻¹ through Teflon tubing (1/4" ID). NO and NO₂ concentra-

<figure><img src="image_2.png" /><figcaption>Figure 1. Leaf area index (LAI) of the wheat and maize crops.</figcaption></figure>

tions were measured by chemiluminescence's analyser fitted with a molybdenum converter (Thermo-Environmental Instruments Inc.; model 42 CTL, Franklin Massachusetts). The detection limit of these analysers was about 50 ppt.

NO fluxes were calculated from the maximum slope of the NO concentration (C) curve over time. The slopes (dC/dt) were estimated with a time step of 60 s, and the overall integrating time was 300 s. Fluxes were estimated according to the following equation:

$$F = \text{Max}\left(\frac{dC}{dt}\right)\frac{V}{S} \quad (1)$$

where V is the chamber volume (82 l), and S the area covered by the chamber (0.25 m²).

For the maize crop, the frames were inserted between the rows. For the wheat, we cut the plants that were too tall to fit inside the chambers.

### Wind tunnel

Wind tunnels have been widely used to measure ammonia volatilization, but not yet to estimate NOₓ and O₃ exchanges above the soil surface. Their performance has largely been discussed (Loubet et al. 1999a, b). The basic principle of this technique is to assess the difference between the input and the output concentration of a gas in the tunnel. The system boundaries for calculating this mass balance are the experimental area (maize or wheat crop), the cover of the wind tunnel, and the inlet and outlet cross-sections of the cover (Figure 2). The mass conservation of the gas then reads:

$$F = \frac{Q(C_o - C_i)}{S} \quad (2)$$

where F is the flux measured (ppb m s⁻¹), Q is the volumetric flow rate (m³ s⁻¹), S the experimental area (m²), and C_o and C_i the mean output and input gas concentrations of the gas (ppb). The wind tunnel was constructed according to the system proposed by Lockyer (1984). The experimental area consisted of 1 m² surface (0.5 m × 2 m), covered with an inverted U polycarbonate sheet, 5 mm thick, with a 85% transmittance for solar radiation between 420 and 750 nm. Note that the cover blocked wavelengths lower than 420 nm, preventing the photolysis of NO₂ known to occur in the 300–420 nm range. Ventilation was provided by a large fan, whose speed was adjusted to yield a flow
<figure><img src="image_3.png" /><figcaption>Figure 2. Wind tunnel design.</figcaption></figure>

rate of 0.255 m³ s⁻¹. The fan was connected to the tunnel through a 0.35 m diameter cylindrical duct. The duct design was optimized to induce uniform wind speed and gas concentrations over the duct section, which was 0.245 m in diameter (Loubet et al. 1999a, b). A hot wire anemometer and an inlet tube were placed in the duct to measure Q and C₀. In order to retain local source of pollutants, a vertical 1.5 m tall shaft was set in front of the tunnel. Inlet air of the wind tunnel then came from the 1.5 m height.

NO and NO₂ concentrations were measured with the same chemiluminescence analyser. O₃ concentrations were measured by an UV absorption analyser (Model O3 41M, Environnement SA; Poissy, France), with a detection threshold of 1 ppb.

### Laboratory data

Soil was sampled from the 0–15 cm layer in 10 replicates, prior to seeding in October 2001. The replicate samples were pooled, dried to about 2% moisture content (w/w), sieved through a 1 mm mesh and stored at 4 °C before use.

Soil incubations were performed at 20 °C under dark conditions in 37 ml air-tight flasks. During the incubations, each flask contained the equivalent of 5 g of dry soil. The gradient of nitrification rate (6 nitrification rates with 3 replicates each) was obtained by adding different amounts of water to soil samples, which resulted in soil moisture levels varying from 9 to 27% (w/w). Ammonium (NH₄⁺) was added as ammonium sulphate at the same time as water to produce a soil concentration of ca. 0.40 mg N g⁻¹ soil, known as non-limiting for the nitrification process. Soil incubations were performed in the surrounding atmosphere. Nitrification rates were determined from the increase in (NO₂⁻ + NO₃⁻)-N occurring in the soil during a

9-day period of incubation (Garrido et al. 2002). Mineral N was extracted with 1 m KCl solution (soil:solution ratio of 1:5) at time zero and after 2, 5, 7, and 9 days of incubation. Nitrate and nitrite concentrations were determined by colorimetric assay using the Griess-Ilosvay reaction (Keeney and Nelson 1982).

### Modelling

In the modelling approach, we focused on the nitrification pathway and computed NO production directly from the nitrification activity, using a linear relationship. The equation reads:

$$NO = aN_i \quad (3)$$

where Nᵢ is the actual nitrification rate (mg NO₃-N kg soil⁻¹ day⁻¹), and NO is the corresponding NO production rate (mg NO-N kg soil⁻¹ day⁻¹), and a is a unit less coefficient. The nitrification rate, Nᵢ, is calculated as the product of three functions expressing the controls by soil humidity, temperature and ammonium content (Hénault et al. 2004):

$$N_i = N_w N_T N_{NH_4} \quad (4)$$

where Nₗ (mg NO₃-N kg soil⁻¹ day⁻¹) is the nitrification response to soil water content. It was determined in the above-described laboratory experiment under controlled conditions (temperature set at 20 °C), with a non limiting ammonium supply, and a water content varying between 9 and 27% (w/w). A linear relationship was observed between nitrification rate and soil water content, viz.:

$$N_w = bW_c + c \quad (5)$$

where W_c is the gravimetric water content (g water g soil⁻¹), b and c are regression coefficients.
$N_T$ is the nitrification response to soil temperature. We used the following relationship from Linn and Doran (1984):

$$N_T = \exp\left[\frac{(T - 20)\ln(2.1)}{10}\right] \quad (6)$$

where T is the soil temperature (°C). This function was adjusted to give a value of unity at 20 °C.

Lastly, $N_{NH_4}$ is the relationship between nitrification rate and ammonium content. We used the following Michaelis kinetics equation:

$$N_{NH_4} = \frac{[NH_4^+]}{km + [NH_4^+]} \quad (7)$$

where $[NH_4^+]$ is the soil ammonium content (mg N kg soil⁻¹) and $km$ is the half-saturation constant (mg N kg soil⁻¹), calculated for different soil water contents (Focht et al. 1978). In the literature, there are few experimental determinations of $km$, and a wide range of values has been reported, varying from <1 to >50 mg N kg soil⁻¹ (Bosatta et al. 1981).

Thus, we fitted the $km$ coefficient using the measured soil moisture, temperature and ammonium data measured in the topsoil layer (0–15 cm) under the wheat and maize crops. Following nitrogen fertilization, when all the fertilizer nitrogen could be considered as dissolved and when plant nitrogen uptake could be neglected, we used equations (4), (5), (6), and (7) to estimate the daily nitrification rate between the soil sampling dates. These periods run from April 30 to May 25 for the wheat, and from May 7 to June 6 for the maize. Each day, the daily calculated nitrification rate was subtracted from the current ammonium pool to calculate soil $NH_4^+$ content for the following day. This calculation was repeated until the date of the next soil ammonium content sampling. The $km$ value was then adjusted to match the calculated and observed soil ammonium content.

## Results and discussion

### Seasonal dynamics under wheat and maize crops

The NO fluxes measured with the chamber method on the wheat from November 2001 to October 2002 are shown in Figure 3. The 44 data varied between 0.3 and 37.1 ng NO-N m⁻² s⁻¹, and had a mean value of 7.4 ng NO-N m⁻² s⁻¹ for the

whole campaign. Emissions were maximum after the two nitrogen fertilizer inputs (on March 8 and April 3), and remained significantly higher than the background emissions for about 3 weeks each time. Outside these periods, emissions remained at background level of a few ng NO-N m⁻² s⁻¹. For the second fertilization, the largest emissions occurred only 20 days after application. This time delay could be explained easily by a lack of rainfall over these 20 days (Figure 3a). The nitrogen fertilizer applied was thus not readily incorporated in the soil. Overall, NO emissions under wheat were higher after the second fertilization compared to the first one, despite the nitrogen input to the soil being only effective 3 weeks after application. Indeed, part of the nitrogen could have been lost by volatilization during the dry period, which was unfavourable to NO production.

Regarding the first fertilization, the cumulative losses of nitrogen as NO gas over 1 month was equivalent to 200 g NO-N ha⁻¹ (from March 8 to April 8), which represents about 0.4% of the nitrogen input. As for the second input, the loss total was 500 g NO-N ha⁻¹, representing about 0.6% of the input. For the second estimate, losses were cumulated only after the first rainfall event when the fertilizer was incorporated into the soil, i.e. from April, 18 to May 18. In terms of nitrogen balance over the 10 months of measurements, the NO-N loss was estimated at 1.4 kg N ha⁻¹ for the wheat crop, which corresponds to 1% of the total N-inputs. At that point we must nevertheless distinguish NO losses due to fertilization from those due to the background mineralization of soil organic nitrogen. For the 300 days of wheat growth, we considered that N fertilizer was effectively present in soil only during 70 days (from March 8 to May 18), corresponding to a mean NO flux of 11 g NO-N ha⁻¹ d⁻¹. Outside this period, the background emissions averaged 2.6 g NO-N ha⁻¹ d⁻¹. Thus, if we subtract the latter contribution to the 10 months NO emissions, we find that only 0.45% of the fertilizer was emitted as NO.

The NO fluxes from the maize crop were measured from April 29 to October 4, using the chamber technique. Fluxes were sampled on 21 dates, and varied between 1.3 and 245.3 ng NO-N m⁻² s⁻¹, with a mean of 56.3 ng NO-N m⁻² s⁻¹ over the whole campaign (Figure 4). In terms of nitrogen balance, the NO-N loss was estimated at 3.8 kg N ha⁻¹ over the 6 months of measurements
<figure><img src="image_4.png" /><figcaption>**Figure 3.** (a) Mean daily NO fluxes measured with chamber method and rainfall during the whole growing period of the wheat crop. (b) Mean daily NO fluxes (chamber method) with nitrate and ammonium contents in the 0–15 cm layer during whole growing period of wheat crop. The mean bulk soil density was 1.21 for this layer. The fertilizer amounts as ammonium or nitrate are also showed.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Figure 4.** Mean daily fluxes monitoring with chamber and wind tunnel method on maize crop compared with the variations of the soil temperature.</figcaption></figure>

for maize crop, corresponding to 2.6% of the total N input. As for the wheat, we distinguished the fertilizer NO losses, from these due to the background mineralization of soil organic N-matter. Over the 187 days of the plant growth, we considered that N fertilizer was effective only during

38 days (from April 25 to June 2), corresponding to a mean NO flux of 86.5 g N-NO ha⁻¹ day⁻¹. Outside this period, the background emission was 2.3 g NO-N ha⁻¹ day⁻¹. If we subtract the latter contribution to the NO emission, we consider that only 2.3% of the NO emission was due to fertilizer application. This ratio is about five times higher than that for the wheat crop. For both crops, the amounts of nitrogen lost as NO gas were consistent with literature data (Skiba et al. 1992, 1997; Davidson and Kingerlee 1997; Veldkamp and Keller 1997; Simpson et al. 1999).

*Comparison between wind tunnel and chamber measurements*

On maize, NO emissions were also monitored every 1/4 h from April 29 to July 28 using a wind
tunnel. Figure 4 shows the mean daily NO emissions obtained with this technique. We observed a good similarity among the emissions, both in magnitude and in variation between the emissions measured by the chamber and by the wind tunnel technique. With the latter technique, the mean value over the whole period was 44.6 ng NO-N m⁻² s⁻¹, with a maximum value of 240.7 ng NO-N m⁻² s⁻¹. Small differences between the two methods could be explained by the fact that the wind tunnel method disturbs emissions by modifying the local turbulence and soil humidity. The sheet of polycarbonate above the enclosed soil area was an obstacle to rainfall, and could alter soil humidity. After each rainfall event and to avoid any water deficit, we irrigated the soil. Nevertheless, the timing of irrigation was not totally equivalent to the rainfall, and could explain the differences observed especially on May 9 and 17. The daily emissions were also not estimated on the same time basis. For the wind tunnel, it was a truly mean daily value while for the chamber method, the values were obtained during the morning or the afternoon only.

## Temperature and rainfall effects

The quarter-hourly fluxes measured with the wind tunnel (Figure 5) indicated a large diurnal variation of emissions, which paralleled the variations in soil surface temperature. We observed an exponential dependence between these two variables. This dependence was quantified over a particular week, from May 13 to May 19.

Instantaneous fluxes were divided by their mean daily value to take into account the variation in NO emissions resulting from other environmental control factors which varied on a larger time scale (i.e. soil nitrogen or water content). We obtained the following relationship between the two variables:

$$ 
\begin{aligned}
\text{Flux}_{\text{no}} &= 0.270(\pm0.010) \exp[0.068(\pm0.002)T] \\
R^2 &= 0.50
\end{aligned} 
\quad (8) 
$$

where T is the surface soil temperature (°C) in the tunnel, and Fluxₙ₀ the normalized flux. This relationship was established with soil temperatures in the range of 10 to 30 °C. The temperature dependence of the NO fluxes is consistent with the previous estimates (Williams et al. 1992), in that it corresponds to a Q₁₀ value of about 2.1. It is similar to the value reported by Linn and Doran (1984), and used in the NO model here. The uncertainty of the emissions' dependence with temperature was linked to the asymmetry of NO emission response to temperature. For all days, the NO flux response was more important during the rising temperature phase in the morning than during the decreasing phase in the afternoon.

On a seasonal time-frame, the differences in NO response between the two fertilization applications on the wheat could be partly explained by soil temperature. From March to May, mean soil temperature at the 8 cm depth indeed increased from 10.5 °C to 13.7 °C. The use of Equation (8) indicates that this 3.2 °C difference should induce a 20% relative increase in the soil NO production rates, which is in agreement with the difference in

<figure><img src="image_6.png" /><figcaption>Figure 5. Quarter hourly NO fluxes measured using the wind tunnel with surface soil temperature on maize crop.</figcaption></figure>
cumulative losses after the two N applications. The same applies when comparing the wheat and maize crops. During the month following the N application on maize (from May 4 to 28), mean soil temperature at the 8 cm depth was 14.7 °C, which favoured larger NO emissions.

Rain was generally observed to stimulate NO emissions, with higher fluxes being recorded after all rainfall events. This is in accordance with numerous studies (Johansson and Sanhueza 1988; Williams et al. 1992). Rainfall also had an indirect effect, in that it dissolved fertilizer granules, thereby making ammonium available to soil nitrifiers and preventing ammonia volatilization. This appears for instance on April 26, when rainfall induced NO emissions to peak two weeks after fertilizer application on the wheat (Figure 3a).

The soil water content during the experiments remained quite low. Based on soil bulk density values measured in each field, these water contents translated as WFPS (water-filled pore space) values generally ranging from 20 to 60% (Figure 6). Under these conditions denitrification rates were probably very low and nitrification can be

considered as the main process involved in NO production.

## Management effects

Beyond climate-induced effects, differences in the response to nitrogen fertilizer application might be related to timing as well as to the form of fertilizer applied. For the wheat crop, the loss as NO during the month after the first application was estimated at 200 g N ha⁻¹, while it was 500 g N ha⁻¹ for the second input. The difference in N losses could be explained by a difference in soil temperature (20%), by the quantity of N applied (50 kg N ha⁻¹ and 80 kg N ha⁻¹ for the first and second fertilization, respectively), but also by the stage of plant development. Indeed, the first fertilization corresponded to the onset of spring growth for the wheat plants. Their LAI increased from 1 to 2 m² m⁻² over the 18 days time interval running, from March 15 to April 2 (Figure 1). After the second application, the growth rate of LAI was approximately halved, rising from 2 to 2.9 between April 2 and May 2. Immediately after the first N application, the N needs of plants were thus higher, leaving less N available to the microorganisms responsible for NO formation. This could explain the lower emissions of NO for this period.

Similarly, the relative differences in NO emissions between the maize and wheat crops may be linked to the timing of fertilizer management with regard to plant development. Application of mineral nitrogen to bare soil, as was the case for the maize crop, is certainly not a practice likely to reduce NO emissions. This makes applied nitrogen fully available to nitrifiers or denitrifiers, and leads to enhanced NO emission. However, it is necessary to prevent leaf and plant damage that may occur when applying liquid forms of fertilizer at a later stage. The differences in NO emission rates measured simultaneously on the two crops from April 25 to June 2 were quite large: the NO fluxes averaged 16 ng NO-N m⁻² s⁻¹ for the wheat and 100 ng NO-N m⁻² s⁻¹ for the maize. Because the comparison was carried out on the same field and during the same time period, these differences should be ascribed to differences in soil mineral nitrogen content. These differences resulted in turn from the doses applied to the crops: 140 kg

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /><figcaption>Figure 6. Water-filled pore space (WFPS) for wheat (a) and maize (b) crops in the 0–15 cm layer.</figcaption></figure>
$N \text{ ha}^{-1}$ (with 105 as ammonium and 35 as nitrate) for the maize, and 80 kg $N \text{ ha}^{-1}$ (with 40 as ammonium and 40 as nitrate) for the second input for the wheat. Nevertheless, a large part of the emission from the two crops (factor of about 6) could certainly be explained by difference in plant nitrogen assimilation between the two crops.

These observations demonstrate the need to use
a 'crop model' to quantify the different nitrogen
fluxes in the soil (mineralization, immobilization,
plant uptake, ...) and their relative effects on the
NO source.

Furthermore, the **type of fertilizer** used could
induce differences in NO emission. For the wheat
crop two different fertilizers were used. Since they
resulted in similar doses of ammonium, totalling
37.5 kg NH₄-N ha⁻¹ and 40 kg NH₄-N ha⁻¹ for
the first and second application respectively, we
may conclude that ammonium nitrate results in
higher NO emissions than the UAN solution.
However, when we compare not only soil tem-
perature between the two periods but also NO
fluxes with NO₃ and NH₄ content variations in the
top 15 cm (Figure 3b), it appears that NO emis-
sions were driven by nitrification kinetics depend-
ing on ammonium content. With high nitrate
content, we sometimes observed low NO emissions
(on March 27 and April 11). In contrast, when the
ammonium content fell to about one mg
N kg soil⁻¹, NO emissions were always low. Fur-
thermore, after crop harvest and incorporation of
wheat straw in the soil by tillage, surface ammo-
nium content was maintained at a low value of
about one kg NH₄-N ha⁻¹ while the nitrate
content rose to 14 kg NO₃-N ha⁻¹ in October as a

result of the mineralization of crop residues. Sur-
prisingly these high levels of nitrate did not lead to
higher NO emissions and reinforced the belief that
an important part of the NO emissions resulted at
first from nitrification. This last conclusion is
reinforced by the maize crop observations. There,
the quantity applied in a single time was high
(140 kg N ha⁻¹), but the high emissions of NO
could be linked to the form of the UAN solution
used. If we consider that the major part of NO
emission occurred by nitrification of the fertilizer,
then the UAN solution favours largest NO emis-
sions. This hypothesis is enhanced by analysis of
NO emission versus soil nitrate and ammonia
content (Figure 7). On the maize, the largest NO
emissions lasted for about one month after fertil-
ization until June 2. Thereafter (on June 6 and 18),
the nitrate content in the 0–15 cm soil layer was
still large, and resulted for a large part to the
nitrification of the 105 kg NH₄-N ha⁻¹ applied on
April 25. The rapid decrease in nitrate content
after early May was then concomitant with plant
growth.

Modelling

The relationship between nitrification rate and soil
water content (Equation 5) was parameterized
from the laboratory data as follows: N<sub>w</sub> = 0.8166
Wc - 6.6868 (R<sup>2</sup> = 0.96; n = 5). It was obtained for a
soil temperature of 20 °C, a non-limiting NH<sub>4</sub><sup>+</sup>
content, and for a soil water content between 9
and 27% (w/w). These water contents are consis-
tent with the soil water contents observed 'in situ'.

<figure><img src="image_9.png" /><figcaption>*Figure 7.* Mean daily NO fluxes (chamber method) with nitrate and ammonium contents in the 0–15 cm layer (bulk soil density of 1.13) during all growing period of wheat crop. The fertilizer amounts as ammonium or nitrate are also indicated.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Figure 8. Comparison of modelled and measured NO fluxes (with tunnel or chamber methods) for wheat crop (a) and maize crop (b).</figcaption></figure>

The km value was fitted to 250 mg N l⁻¹ for the two crops. This value corresponds to 50 mg N kg soil⁻¹ for a soil water content of 20% (w/w).

Next, we estimated the coefficient a appearing in Equation (3) by regressing the NO fluxes measured either with the wind tunnel or the chamber methods against the nitrification rates calculated above. We thereby assumed that only the top 15 cm of soil contributed to NO emissions. We obtained the following relationships:

$$NO = 1.61(\pm0.09)\%N_i \quad R^2 = 0.90; n = 14 \quad (10)$$

for the maize crop with wind tunnel NO data

$$NO = 1.90(\pm0.11)\%N_i \quad R^2 = 0.92; n = 17 \quad (11)$$

for the maize crop with chamber NO data

$$NO = 1.48(\pm0.16)\%N_i \quad R^2 = 0.53; n = 27 \quad (12)$$

for the wheat crop with chamber NO data

where NO is NO emission rate (mg NO-N kg soil⁻¹) and Nᵢ the nitrification rate (mg NO₃⁻-N kg soil⁻¹).

For the three equations we observed a good correlation between these two variables, and the

similar slope coefficients (around 1.6%). The variability in the latter may be related to uncertainties of NO flux measurements at field scale, or to processes not considered in the NO emission algorithm (i.e. nitrogen uptake by plant, modification of soil pH by fertilizer N, or NO emissions by denitrification). Figure 8 compares the measured and modelled NO emissions obtained for the wheat and maize crops. Modelled NO fluxes were estimated directly from the above regression equations.

Although the model only simulated NO production through the nitrification pathway, a good match between modelled and measured emissions was observed. It could be explained by the fact that conditions were seldom conducive to denitrification, since WFPS rarely exceeded the 60% threshold water conditions as reported by Parton et al. (2001) and Linn and Doran (1984), (Figure 6). Even when WFPS was above 60% (in late November, December and late February), other environmental conditions were not conducive to NO production, since soil mineral N and soil temperature were low. It is
thus likely that NO production occurred mostly through nitrification.

Using the nitrification algorithm we tested the relative weights of the functions $N_w$, $N_T$, $N_{NH_4}$ in NO production variability. Tables 1 and 2 give the relative contributions to the NO emission variation of these functions. Whatever the crop, the ammonium function $N_{NH_4}$ had a major contribution (~69%). It also appeared essential to determine the value of the half saturation coefficient (km) with a high accuracy. An indirect estimation of this coefficient in the field, as was done here should be corroborated by laboratory experiments under controlled moisture and temperature conditions, involving a large gradient of $NH_4^+$ concentrations. For the wheat crop, soil temperature was the second contributor to the NO variability, which may be explained by the wide range of soil temperatures experienced by the soil during the wheat growing season (from winter to summer). For the maize crop the contributions of the $N_T$ and $N_w$ function were similar (ca. 14%).

## Conclusions

Our measurements highlighted a large dependence of NO emissions on mineral nitrogen fertilization:

emissions were largest during the few days following nitrogen inputs, with mean daily rates greater than 300 g N ha⁻¹ day⁻¹. A time lag of a few days was related to the kinetics of nitrogen fertilizer incorporation in the soil, which is linked to the occurrence of rainfall. The emissions measured on the maize field were higher than on the wheat field. The difference was linked to nitrogen input management. For the maize crop, nitrogen was applied before plant emergence, and was thus fully available to the soil micro-organisms responsible for NO production. The increase of NO emissions after the N inputs lasted about one month in both cases. After this period, we observed a return to background emissions of a few g N ha⁻¹ day⁻¹, as before fertilizer application. In terms of nitrogen balance, the N losses were estimated at 1.4 kg N ha⁻¹ (1.0% of the total N-input over the 10 months of measurements) for the wheat, and 3.8 kg N ha⁻¹ (2.6% of the N-input over the 6 months of measurements) for the maize crop. The differences between the two crops could also be linked to the respective growing seasons of the plants. Indeed, a large correlation was observed between soil temperature and NO emissions, with a $Q_{10}$ of about 2.1. This means emissions are likely to be higher with spring crops like maize.

<table><caption>Table 1. Contribution of the different functions $N_T$, $N_w$ and $N_{NH_4}$, on the nitrification rate ($N_i$) under maize.</caption><thead><tr><th>Date</th><th>N<sub>T</sub></th><th>Nw, mg N kg soil<sup>-1</sup> d<sup>-1</sup></th><th>N<sub>NH_4</sub></th><th>N<sub>i</sub>, mg N kg soil<sup>-1</sup> d<sup>-1</sup></th><th>NO × 100, mg N kg soil<sup>-1</sup> d<sup>-1</sup></th></tr></thead><tbody><tr><td>29/4</td><td>0.603</td><td>12.738</td><td>0.147</td><td>1.128</td><td>0.866</td></tr><tr><td>3/5</td><td>0.618</td><td>15.184</td><td>0.133</td><td>1.245</td><td>1.309</td></tr><tr><td>7/5</td><td>0.573</td><td>11.972</td><td>0.598</td><td>4.105</td><td>8.617</td></tr><tr><td>13/5</td><td>0.696</td><td>12.738</td><td>0.488</td><td>4.324</td><td>6.861</td></tr><tr><td>15/5</td><td>0.750</td><td>12.893</td><td>0.443</td><td>4.287</td><td>9.176</td></tr><tr><td>17/5</td><td>0.972</td><td>12.834</td><td>0.392</td><td>4.885</td><td>11.677</td></tr><tr><td>21/5</td><td>0.975</td><td>12.719</td><td>0.279</td><td>3.459</td><td>5.391</td></tr><tr><td>23/5</td><td>0.754</td><td>13.310</td><td>0.217</td><td>2.180</td><td>2.024</td></tr><tr><td>30/5</td><td>0.706</td><td>13.032</td><td>0.100</td><td>0.921</td><td>0.603</td></tr><tr><td>6/6</td><td>0.771</td><td>13.700</td><td>0.016</td><td>0.168</td><td>0.229</td></tr><tr><td>12/6</td><td>0.857</td><td>12.755</td><td>0.017</td><td>0.182</td><td>0.128</td></tr><tr><td>19/6</td><td>1.177</td><td>9.831</td><td>0.020</td><td>0.227</td><td>0.178</td></tr><tr><td>8/7</td><td>0.872</td><td>9.017</td><td>0.021</td><td>0.162</td><td>0.126</td></tr><tr><td>19/7</td><td>0.899</td><td>8.147</td><td>0.022</td><td>0.159</td><td>0.082</td></tr><tr><td>29/8</td><td>0.851</td><td>9.834</td><td>0.050</td><td>0.419</td><td>0.092</td></tr><tr><td>17/9</td><td>0.704</td><td>8.085</td><td>0.050</td><td>0.285</td><td>0.070</td></tr><tr><td>4/10</td><td>0.560</td><td>6.951</td><td>0.054</td><td>0.210</td><td>0.060</td></tr><tr><td>σ/m</td><td>0.14</td><td>0.14</td><td>0.72</td><td></td><td></td></tr></tbody></table>

The NO column corresponds to the values of NO emissions measured with the chamber method. The last line ($\sigma/m$) corresponds to the coefficients of variation of the different terms ($N_T$, $N_w$ and $N_{NH_4}$). These three coefficients were normalized to give a sum of 100%. They indicate the relative contribution of the three variables: soil temperature, humidity and ammonium content into the nitrification rate and also to the NO production variability.
<table><caption>Table 2. Contribution of the different functions $N_T$, $N_w$ and $N_{NH_4^+}$ on the nitrification rate ($N_i$) under wheat.</caption><thead><tr><th>Date</th><th>N<sub>T</sub></th><th>N<sub>w</sub>, mg N kg soil<sup>-1</sup> d<sup>-1</sup></th><th>N<sub>NH<sub>4</sub></sub></th><th>N<sub>i</sub>, mg N kg soil<sup>-1</sup> d<sup>-1</sup></th><th>NO×100, mg N kg soil<sup>-1</sup> d<sup>-1</sup></th></tr></thead><tbody><tr><td>12/12</td><td>0.291</td><td>17.020</td><td>0.010</td><td>0.049</td><td>0.202</td></tr><tr><td>3/1</td><td>0.229</td><td>14.038</td><td>0.014</td><td>0.046</td><td>0.076</td></tr><tr><td>23/1</td><td>0.375</td><td>15.397</td><td>0.007</td><td>0.040</td><td>0.009</td></tr><tr><td>19/2</td><td>0.344</td><td>15.685</td><td>0.006</td><td>0.034</td><td>0.079</td></tr><tr><td>7/3</td><td>0.471</td><td>15.992</td><td>0.032</td><td>0.243</td><td>0.374</td></tr><tr><td>11/3</td><td>0.419</td><td>15.474</td><td>0.033</td><td>0.213</td><td>0.303</td></tr><tr><td>28/3</td><td>0.408</td><td>15.531</td><td>0.056</td><td>0.352</td><td>0.704</td></tr><tr><td>5/4</td><td>0.539</td><td>11.976</td><td>0.042</td><td>0.271</td><td>0.396</td></tr><tr><td>11/4</td><td>0.456</td><td>9.849</td><td>0.047</td><td>0.211</td><td>0.307</td></tr><tr><td>29/4</td><td>0.603</td><td>8.901</td><td>0.136</td><td>0.729</td><td>0.962</td></tr><tr><td>30/4</td><td>0.591</td><td>8.879</td><td>0.154</td><td>0.809</td><td>1.622</td></tr><tr><td>2/5</td><td>0.696</td><td>10.323</td><td>0.147</td><td>1.059</td><td>0.780</td></tr><tr><td>6/5</td><td>0.601</td><td>11.072</td><td>0.095</td><td>0.631</td><td>0.590</td></tr><tr><td>7/5</td><td>0.573</td><td>10.633</td><td>0.087</td><td>0.531</td><td>1.761</td></tr><tr><td>13/5</td><td>0.696</td><td>10.576</td><td>0.039</td><td>0.285</td><td>0.868</td></tr><tr><td>15/5</td><td>0.723</td><td>10.509</td><td>0.029</td><td>0.220</td><td>0.803</td></tr><tr><td>17/5</td><td>0.766</td><td>9.173</td><td>0.023</td><td>0.165</td><td>0.359</td></tr><tr><td>21/5</td><td>0.772</td><td>8.956</td><td>0.014</td><td>0.094</td><td>0.280</td></tr><tr><td>23/5</td><td>0.679</td><td>11.132</td><td>0.009</td><td>0.067</td><td>0.197</td></tr><tr><td>6/6</td><td>0.720</td><td>15.486</td><td>0.012</td><td>0.136</td><td>0.147</td></tr><tr><td>19/6</td><td>0.993</td><td>8.756</td><td>0.017</td><td>0.152</td><td>0.230</td></tr><tr><td>20/6</td><td>0.926</td><td>9.503</td><td>0.017</td><td>0.147</td><td>0.230</td></tr><tr><td>8/7</td><td>0.857</td><td>11.287</td><td>0.012</td><td>0.118</td><td>0.179</td></tr><tr><td>19/7</td><td>0.954</td><td>13.498</td><td>0.017</td><td>0.213</td><td>0.150</td></tr><tr><td>29/8</td><td>0.961</td><td>13.305</td><td>0.011</td><td>0.138</td><td>0.113</td></tr><tr><td>17/9</td><td>0.791</td><td>12.095</td><td>0.011</td><td>0.109</td><td>0.109</td></tr><tr><td>4/10</td><td>0.705</td><td>10.582</td><td>0.012</td><td>0.086</td><td>0.072</td></tr><tr><td>σ/m</td><td>0.20</td><td>0.13</td><td>0.66</td><td></td><td></td></tr></tbody></table>

The NO column corresponds to the values of NO emissions measured with the chamber method. The last line ($\sigma/m$) corresponds to the relative variability of the different terms ($N_T$, $N_w$ and $N_{NH_4^+}$). These three coefficients were normalized to give a sum of 100%. They indicate the relative contribution of the three variables: soil temperature, humidity and ammonium content into the nitrification rate and also to the NO production variability.

Although the used simple model simulated only nitrification-mediated NO production, comparison between measured and modelled NO fluxes was very satisfactory, both in magnitude and in time variation after fitting the half saturation coefficient of the ammonium nitrification function. This good agreement could be explained by the low soil water contents prevailing under our experimental conditions, minimising the role of denitrification. Future investigations will be necessary to estimate NO production by denitrification in the laboratory under anaerobic conditions, and *in situ* with hydromorphic soils. Based on these results, the effect of fertilizer type on NO emission should also be a very interesting field of investigation. Future studies will also include the integration of this model for various crop managements and climates and extrapolation of these results to a global scale.

## Acknowledgments

Support of this research was provided by the PNCA (Programme National de Chimie Atmosphérique, INSU), and the GICC (Gestion et Impact des Changements Climatiques, MEED) national programs.

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