Introduction
Agricultural soils represent an important source of atmospheric nitric oxide
(NO), especially in highly fertilised regions (Oikawa et al., 2015). Global
estimates of total NOx (NO + NO2) emissions from soils range
between 4 and 21 Tg N yr-1, which represents between 10 and 15 %
of the global NOx budget (Davidson and Kingerlee, 1997; IPCC, 2001;
Yienger and Levy, 1995). NOx inventories are subject to error in
magnitude and especially in spatial distributions (Martin et al., 2003),
which can be constrained by satellite observations and range around 30 %
at the global scale (Toenges-Schuller et al., 2006). NOx emissions are
of considerable interest also for atmospheric photochemistry, and acting as
ozone (O3) precursors, they indirectly have an impact on climate.
O3 is indeed an important greenhouse gas,
contributing to 25 % of the
anthropogenic net radiative forcing (IPCC, 2007).
NOx, and especially NO2, are toxic gases for humans, exposure
to
which increases risks of various respiratory diseases. The World Health
Organization gives guidelines for NO2 exposure limits, both annual means
(40 µg m-3) and 1 h mean (200 µg m-3)
(Prüss-Üstün et al., 2016). For O3, only a short-term
threshold is given (100 µg m-3 for the 8 h mean) because
there are fewer studies on long-term exposure. These thresholds are
established both in epidemiological and toxicological studies on humans and
animals. Similarly, nitrogen deposition leads to serious adverse effects on
the ecosystem (eutrophication, biodiversity erosion and acidification being the
most serious ones), while O3 has a direct adverse effect on plant health
through oxidation of photosynthesis pathways and direct tissue destruction
above large thresholds. For nitrogen, the concept of critical load has been
developed which gives the amount of nitrogen deposition above which an
ecosystem is impacted. These critical loads range from
5 kg N ha-1 yr-1 for sensitive habitats to
20 kg N ha-1 yr-1 for less sensitive ones (APIS, 2016). For
these reasons, national and international authorities regulate atmospheric
levels of these pollutants.
NOx emissions from soils are primarily the by-products of nitrification
and denitrification processes and the chemical decomposition of HNO2
(Laville et al., 2005; Meixner, 1997; Remde et al., 1989). Many authors
emphasise that for most agricultural soils, nitrification is the dominant
process of NO emissions (Bollmann et al., 1999; Dunfield and Knowles, 1999;
Godde and Conrad, 2000). Organic and mineral fertilisers, rich in ammonium,
increase NO emissions both by stimulating NO production by nitrification and
by decreasing NO consumption.
There is a significant knowledge gap in understanding NOx
exchanges
between agricultural ecosystems and the atmosphere, partly due to a lack of
direct measurements over long periods. NO emissions by soils can either be
measured by dynamic chambers (Breuninger et al., 2012; Laville et al., 2009,
2011; Pape et al., 2009), aerodynamic gradient (Kramm et al., 1991), or eddy
covariance methods (Rummel et al., 2002; Stella et al., 2013a). Each method
has its drawbacks and challenges. The dynamic chamber method may change the
surface exchange parameters (Pape et al., 2009), and modify the fluxes due to
fast reactions between the triad O3–NO–NO2, but thoroughly designed
Teflon chambers can overcome this problem (Skiba et al., 2009). The
aerodynamic gradient method (AGM) is a well-established method applicable to
water-soluble compounds such as NH3 (Milford et al., 2009), but has
several biases of which flux divergence due to chemical reactions is the most
limiting for NO–NO2–O3 (Duyzer et al., 1995; Kramm et al., 1991;
Loubet et al., 2013). Non-stationarity and integration time are also limiting
(Lenschow et al., 1994; Stella et al., 2012). The eddy covariance method is
adapted for measuring NO fluxes. It is however also vulnerable to flux
divergence issues due to NO–NO2–O3 chemical reactions. It is
therefore essential to measure the fluxes and mixing ratios of the three
compounds together.
The eddy covariance (EC) method is the state-of-the-art flux measurement
method for energy and CO2 fluxes (Baldocchi, 2003), and due to the
development of new analysers such as fast chemiluminescence, quantum cascade
lasers, absorption spectroscopy, or proton time-of-flight mass spectrometers
(Ammann et al., 2012; Brodeur et al., 2009; Ferrara et al., 2012; Li et al.,
2013; Müller et al., 2010; Park et al., 2014; Peltola et al., 2014;
Sintermann et al., 2011; Stella et al., 2013a; Wolfe et al., 2009) it can
currently be applied to several other trace gases. The main advantage of the
EC method is that it is a “direct” measurement of the flux at a given
height, which depends on fewer assumptions than the AGM, namely the Reynolds
averaging and ergodicity hypothesis requiring that “the averaging time must
be much larger than the timescales of variation of the air velocity”
(Corrsin, 1975, see also Kaimal and Finnigan, 1994). This method has been
successfully applied for measuring NO fluxes in a limited number of studies
(Eugster and Hesterberg, 1996; Lee et al., 2015; Marr et al., 2013; Min et
al., 2014; Rummel et al., 2002; Stella et al., 2013a). The main difficulties
of EC measurements are the losses that appear at high frequencies due to
adsorption of the gas to the tubing system, which depends also on the size of
the absorption cell (Eugster and Senn, 1995) and differential advection
caused by the radial variation of the mean velocity and simultaneous radial
diffusion of the sample gas (Lenschow and Raupach, 1991). Moreover, since
NO2-to-NO photolytic converters typically applied in combination with
chemiluminescence analysers have a conversion efficiency below 100 %,
measuring both NO and NO2 with such a converter remains a challenge that
requires the use of two analysers simultaneously (Lee et al., 2015).
Due to these limitations, simultaneous measurements of NO, NO2 and
O3 fluxes by EC have hence seldom been made. To our
knowledge, only a few studies report such measurements and none over an
arable crop. There is therefore a gap in knowledge as to whether the
reactions between NO, NO2 and O3 significantly influence the fluxes
above crops and how nitrogen application modifies these fluxes and their
interactions. Eugster and Senn (1995) report NO2 fluxes by EC and analyse the errors of the method. Most studies conducted over
forests show moderate to large in-canopy reactions: Andreae et al. (2002)
report comprehensive flux measurements in the Amazonian forest showing
evidence of within-forest cycling of the nitrogen oxides emitted from the
soil. Horii et al. (2004) report NOx and O3 fluxes over a temperate
deciduous forest showing consistent NOx deposition. Geddes and
Murphy (2014) report such measurements over two mixed hardwood forests in
North America, under a very low NO concentrations regime, which show mainly
NOx deposition with evidence of chemical reactions in the canopy. Min et
al. (2014) report such flux measurements over ponderosa pines which shows
evidence of within-canopy chemical removal of NOx. Ammann et al. (2012)
report total reactive nitrogen fluxes by EC above grassland
which compared well with dynamic chamber NO and NO2 fluxes during
periods with no NH3 emissions. Lee et al. (2015) and Marr et al. (2013)
report fluxes of NO and NO2 over urban areas which differ in their
comparison with national emissions inventories: while Lee et al. (2015) found
fluxes 80 % higher than national inventories, the second study found
similar fluxes but with large disparities at the local scale.
In this study we are addressing the following questions: (1) is the EC method suitable for quantifying the seasonal dynamics and diurnal
cycles of the NO, NO2 and O3 fluxes above a crop rotation? (2) How
are organic and mineral fertilisations affecting these fluxes and their
dynamics? (3) To what extent are the chemical reactions between NO, NO2
and O3 modifying the fluxes above the ground? And finally, (4) why is
O3 deposition increasing following organic fertilisation? Is that a
consequence of interactions with NO emissions?
To answer these questions we report measurements of NO, NO2 and O3
fluxes by EC using a system similar to Lee et al. (2015) for 1 month following slurry spreading over a bare soil at the FR-GRI FLUXNET and
ICOS site (Loubet et al., 2011). The NO and O3 fluxes were measured over
an additional 6-month period to study the seasonality of these fluxes and to
measure the fluxes following application of mineral fertiliser.
Materials and methods
Site description and management
The experiment took place in a 19 ha field located at Grignon
(48∘51′ N, 1∘58′ E), 40 km west of Paris (France) and
lasted more than 7 months from 7 August 2012 to 13 March 2013. The field was
surrounded by heavy traffic roads on the east, south and southwest. The
field belongs to a large farm (buildings at around 450 m to the southwest)
with around 210 dairy cows, 500 sheep, and a production of approximately 900
lambs. The terrain has a gentle slope of ∼ 1 % and the mean annual
temperature and precipitation were 10.9 ∘C and 575 mm between 2005
and 2013. The main wind directions are northwest during clear days and
southwest during cloudy and rainy days. The soil type is a Luvisol
or loamy clay (25 % clay, 70 % silt, 5 % sand in the top 15 cm).
The soil organic carbon content was ∼ 20 g C kg-1, pH (in
water) = 7.6, and bulk soil density was 1.3 g m-3, in agreement
with previous measurements on the same site (Laville et al., 2009, 2011;
Loubet et al., 2011). High pH values are common in soils over calcareous
layers and with high fine fraction content (clay and silt) as is the one of
the Grignon site. Indeed, alkalinity fosters the nitrification process and
this range of pH is optimum for it to occur (e.g. Nieder and Benbi, 2008). A
detailed description of the site can be found in Laville et al. (2009, 2011)
and Loubet et al. (2011).
(a) Simplified map of the FR-GRI
field site showing the mast and surrounding roads. The colours correspond to
elevation. (b) Simplified sketch of the instrumental setup to
measure EC fluxes. Gill R3 is the ultrasonic anemometer, Li7500 is the open-path infrared CO2 and H2O gas analyser, the rain cup is the air
sampler for NO and NO2 detection. CLD780-TR NO and NOx are the
fast-response NO analysers (Ecophysics) operating in parallel, one connected
to a BLC measuring NO + αNO2. The NO, NO2 and O3
slow analysers (Thermo Scientific, Waltham, USA) are placed behind a Teflon
pump ensuring atmospheric pressure at the inlet. A large pallet pump ensured
a flow rate of 80 NL min-1 in the heated inlet line. Teflon filters
(1 µm) were installed at the front of the instrument inlets (purple
cylinders).
The field was cultivated with winter wheat (a mix of Atlass and Premio
species), which was harvested on 3 August 2012 (16.7 Mg ha-1 of dry
matter). Cattle slurry was applied on the field with a trailing hose from
18 to 19 August 2012, at a rate of 42 kg N ha-1 of which 78 % was
ammonium (NH4+). The slurry had a very low dry matter content of
3.2 % and a C / N ratio of 15.7. The total C applied was
666 kg C ha-1. A gentle tillage was performed on 29 August 2012
to incorporate the crop and slurry residues and prepare the soil for oilseed
rape sowing (variety Adriana) at a density of 35 plants per square metre. The
crop developed slowly during the winter with a dry matter above ground (leaf
area index) of 37 g m-2 (0.65 m2 m-2) on 25 October 2012 and 104 g m-2 (0.7 m2 m-2) on the
18 February 2013. The canopy height stayed below 10 cm during the whole
winter. Ammonium nitrate pellets were applied on the oilseed-rape field on
20 February 2013 at a rate of 54 kg N ha-1. Two selective
herbicides were applied on the 2 (Springbok: 200 g L-1 of metazachlor;
200 g L-1 of DMTA-P at 3 L ha-1) and 31 October 2012
(Devin/cycloxydim: 100 g L-1 at 1 L ha-1) which only destroyed
the weeds. In December 2012 slug-repellent pellets were applied.
Micrometeorological and ancillary measurements
Meteorological measurements included wind speed, wind direction, air and soil temperatures
and humidity as well as rainfall, global, net and photosynthetic active
radiation. The meteorological measurements were performed on a mast (3.17 m
high) near the centre of the field and close to the flux measurement site
(Fig. 1). Soil was sampled approximately once a month for water content,
total nitrogen and mineral nitrogen analysis. Measurements are described in
Loubet et al. (2011) and will not be detailed here.
A simplified sketch of the EC measurement system is shown in Fig. 1.
Three-dimensional wind and temperature fluctuations were measured near the
centre of the field at 3.17 m above ground by a sonic anemometer (Gill R3
3-axis anemometer, Gill Instruments Limited, UK). A fast response open-path
CO2 / H2O infrared gas analyser (IRGA LI-7500A, LI-COR, USA)
installed at a lateral distance of around 0.2 m to the sonic path measured
CO2 and H2O fluctuations. O3 mixing ratios were measured by a
high-frequency, dry chemiluminescence O3 detector (NOAA, USA) and its
Teflon PFA inlet tube (length = 2.8 m, internal diameter = 0.32 mm)
was positioned in-between the sonic path and the IRGA at a lower height. The
high-frequency signals were recorded at 20 Hz by a Labview program developed
in the laboratory. In accordance with Lee et al. (2015), high-frequency
(10 Hz) time series of NO and NO2 were determined by two fast-response
and closed-path chemiluminescence NO analysers (CLD 780TR, EcoPhysics,
Switzerland), one being coupled to a photolytic converter (blue light
converter, BLC, Droplet Measurement Technologies Inc, USA) for the detection
of NO2 (see Fig. 1). The horizontal separation of the trace gas inlets
from the sonic path was 20 cm. Air was sampled through two heated and shaded
PFA tubes with a length of 20 m and an inner diameter of 9.55 mm. The first
CLD was used for measuring NO and the second one connected to the BLC was
used for detecting NO2. Conversion efficiencies for NO2 to NO of
around 30 % were achieved. The high-frequency signals of NO, NO2 and
O3 were calibrated with mixing ratios measured at 30 min time resolution
by slow-response analysers (Thermo Scientific, Waltham, USA) (Fig. 1). These
instruments were calibrated every 3 to 6 weeks using the gas-phase titration
(GPT) method and a 17 ppm NO standard (Air Liquide, FR). The fetch of the
field site extended at least to 150 m in all directions and a footprint
analysis showed that 90 % of the time the entire field was in the
footprint during neutral and moderately stable or unstable conditions (Loubet
et al., 2011). NO and O3 fast sensors were functioning during the whole
campaign (7 August 2012 to 13 March 2013) together with NO, NO2 and
O3 slow-response analysers and the meteorological station. High-frequency NO2 measurement was performed from 14 August to
30 September 2012. In this study we focus on two periods: (1) from 14 to
29 August 2012 during which all fluxes were measured and NO fluxes were the
highest, in order to investigate the interactions between the fluxes and
mixing ratios of the NO–NO2–O3 triad, and (2) over the whole period
for NO fluxes analysis.
Hourly averaged high-frequency loss correction factors for O3,
NO and NOx over the 15 August–7 September 2012 period determined with
the in situ ogive method. The corrected flux equals the measured flux
multiplied by the correction factor. Black bars are medians, boxes show the
interquartile, error bars show the minimum and maximum of the whisker and
empty dots shows the outliers.
Eddy covariance flux computations
The turbulent fluxes were computed as the covariance between the fluctuations
of the scalar of interest and the vertical component of the wind. As the EC
method and its theoretical background are described in the literature – e.g.
Foken (2008) – details will not be provided here.
For closed-path sensors (NO, NO2 and O3), the lag time between w′
and the dry mole fraction χ had to be determined. This was done by
searching for the maximum of the covariance function
(χw′(t)′(t-lag)‾.
The lag for NO was 3.1 s [2.4–3.65 s] (Q50
[Q25–Q75]), for NO2 it was 4.0 s [3.65–4.55 s] and for O3 it was
2.9 s [2.5–3.25 s]. The lag was filtered for outliers (points outside of
median lag ± standard deviation were considered as outliers) and the
covariance was computed as the value of the covariance function at the
filtered lag.
As fast-response sensors for NO, NO2 and O3 were not absolute, the
fluxes were computed following the ratio method for O3 described by
Muller et al. (2010), and in accordance with Lee et al. (2015) for NO and
NO2:
χFO3=χO3‾Vdryw′O3′‾O3‾,FNO=w′NO′‾SNOVdry,FNO2=1αVdryw′NOx′‾SNOx-w′NO′‾SNO,
where O3 (in mV), NO and NOx (in counts s-1) are the
uncalibrated fast signals, χO3‾ is the 30 min average of the
slow-sensor reference O3 mixing ratio (in ppb), while SNO and
SNO2 are the sensitivity of the analysers (in
counts s-1 ppb-1). The α is the blue light converter
conversion efficiency, and Vdry is the molar volume of dry air (in
m3 mol-1). All fluxes (momentum, heat, CO2, H2O, NO,
NO2, O3) were computed by the EddyPro software-version 5
(http://www.licor.com/eddypro) and final flux data were averaged for
30 min intervals. Evaluation methodologies from the CarboEurope project were
applied – see Aubinet et al. (2000) and Loubet et al. (2011).
Spectral corrections and flux uncertainties
Spectral attenuation of the flux is due to differential transport time of the
compound in the tube and interaction with tube walls and filter surfaces
(Massman and Ibrom, 2008). We tend to minimise this effect by ensuring a
large flow rate in the tubes with a Reynolds number well above the critical
threshold for turbulence – see Lenschow and Raupach (1991) – as well as
heating the tubes to around 5 ∘C above ambient temperature. The
residence time of the air samples inside the tubing was around 1 s, ensuring
low chemical conversions, and the Reynolds number was 11 700, hence largely
in the turbulent range (Re > 4000). However, water vapour
interaction is still expected, and sensor separation also generates high-frequency losses.
The NO, NO2 and O3 random instrument noises were estimated as the
1σ random uncertainty of the signals as in Lenschow et al. (2000), Langford
et al. (2015) and Mauder et al. (2008). This is assumed to be “white noise”
and hence uncorrelated with itself apart from at lag = 0 s. It is therefore
estimated as the difference between the autocorrelation at lag = 0 s and
at lag = ±0.05 s. The flux random uncertainty was itself evaluated
as the covariance detection limit. It was determined as the root mean square
error of the covariance function over 60 s periods at lag times well away
from the position of the time lag. In practice, these were taken at lags
larger than 120 s as absolute values, as proposed by Langford et al. (2015).
Chemical reactions, timescales and flux divergence
Chemical reactions between NO, NO2 and O3 are important to consider
when interpreting the measured fluxes as they can affect the fluxes above the
ground. A common way to determine whether these reactions may indeed affect
the flux is through comparison of chemical and transport timescales. Details
of the reactions rates, timescales and flux divergence calculations are
given in Sects. S1–S3 in the Supplement.
Daily variations of the ratio of the random uncertainty to the flux
for H2O, O3, NO and NOx during August 2012 (15 August to
9 September). Black bars are medians, boxes show the interquartile,
error bars show the minimum and maximum of the whisker and empty dots shows
the outliers.
Results and discussion
Quality check and uncertainties in NO, NO2 and O3 flux
measurements
NOx and O3 half-hourly fluxes were filtered by the quality check test
included in EddyPro (http://www.licor.com/eddypro), according to the
0–1–2 labelling proposed by Mauder and Foken (2006), which includes tests
for stationarity and for well-developed turbulence. As recommended in the
framework of the CarboEurope project, we discarded fluxes with a quality
check index value of 2. This led to keeping 74, 84 and 76 % of the
records for NO, O3 and NO2, respectively. The total records of NO
and O3 half-hourly fluxes were 11 329 (from 7 August 2012 to
13 March 2013), while for NO2 they were 2257 (during the period
14 August to 30 September 2012).
The largest systematic uncertainties were the high-frequency losses, which
were estimated with the in-situ ogive method (Ammann et al., 2006), and
amounted to 10 % for O3, 20 % for NO and 30 % for NO2
on average over the August–September period (when all fluxes were measured,
see Fig. 2). As a bias, they can be corrected for, as in
the following sections of this paper.
The second largest uncertainties were the random uncertainties which were
lower than 20 % in most cases for O3, NO (and similar to H2O)
and around 30 to 40 % for NO2 (Fig. 3). For NO and NO2 the
random uncertainties peaked during the morning traffic hour around
06:00–08:00 UTC, which is explained by the non-stationarity generated by
the local traffic on the mixing ratios. Hence overall the EC
method proved to be usable for measuring NO fluxes over part of the season
with an overall uncertainty similar to H2O. A higher random uncertainty
was found for NO2 fluxes which were smaller than NO fluxes and with a
relatively low conversion ratio from NO2 to NO (30 %).
Meteorological conditions
Daily averages of the air temperature decreased during the measurement
period, starting from about 20 ∘C in summer and reaching minima
around -5 ∘C from December to March. Daily averages of global
radiation decreased from 250 W m-2 in August to around
0 W m-2 in December, back to around 150 W m-2 by the end of
March. The daily average of the relative humidity was around
65 % in August and September, and it increased to about 85 % for the
rest of the period (Fig. 4). The wettest period was between October and November, and
cumulative rain was 319 mm over the 7-month period, which is quite high. The
prevailing wind direction was southwest while the most intense winds were
observed from north and south (Fig. S2 in the Supplement). Figure S2 also
shows that wind regimes were quite different in summer and winter: prevailing
wind directions during August and February were from the southwest and
northeast, respectively. Soil water content (SWC) ranged between 20 and
40 % (volume) (Fig. 4), with a long period between October and January
with values around 28 %, and increased further in January to 35 %,
with sharp decrease during some periods.
Meteorological and soil conditions (daily averages, sums for
rainfall), NO, NO2 and O3 mixing ratios and fluxes during the
entire measurement period from 7 August 2012 to 13 March 2013 at the Grignon
field site. Averages for night-time and daytime are also given as dotted
lines. Rg is the global radiation, Ta and Tg
the air and ground temperature, SWC the soil water content, ws the wind
speed, RH the air relative humidity.
Seasonal dynamics and diurnal cycles of the NO, NO2 and
O3 fluxes above the crop rotation
Seasonal dynamics of NO–NO2–O3 mixing ratios
Average daily NO, NO2 and O3 mixing ratios were 3.6, 6.9 and
24.8 ppb, respectively. The NO and NO2 mixing ratios were higher when
winds blew from the east (from the direction of Paris), while O3 showed
the opposite behaviour, which can be explained by depletion of O3 by NO
sources from the surrounding traffic (as shown in Fig. S2) and by reactions
(Sects. S1–S2). Daily NO2 / NOx ratios were on average
66 %, which is typical for traffic and urban pollution (Carslaw, 2005;
Minoura and Ito, 2010), and ranged from 4 to 93 % during the entire
period. The NO2 mixing ratios were significantly higher (Student t test
p value lower than 8 × 10-11) than the NO mixing ratios in
August and early September, end of January and mid-February, and end of
March. During sporadic episodes, NO peaks were of the same order or even
higher than NO2 peaks (Fig. 4).
Seasonal dynamics of NO, NO2 and O3 fluxes
The daily averaged NO fluxes were very small, except during a period of
strong emission following organic fertilisation over two days in August
(18–19 August 2012), with maximum daily average fluxes of around
1.5 nmol m-2 s-1 (Fig. 4). Other
emission episodes, including
mineral fertilisation in February (20 February 2013), were characterised by
mean daily fluxes below 0.5 nmol m-2 s-1. The NO fluxes were
slightly negative for some events (Q25, Q50 and Q75 equal to
-0.013, 0.031 and 0.11 nmol m-2 s-1, Fig. S3). The O3
fluxes ranged between -13.8 and 0 nmol m-2 s-1, and averaged
to -3.12 nmol m-2 s-1. The largest O3 deposition fluxes
were observed following organic fertilisation in August, and were correlated
with the highest NO emissions. This period also corresponded to large daily
O3 mixing ratios (Fig. 4). The NO2 fluxes were only measured during
the first one and a half months (14 August to 30 September 2012) and were
mostly negative (indicating deposition), except during the first week
following organic fertilisation (Q25, Q50 and Q75 equal
-0.11, -0.07 and 0.08 nmol m-2 s-1) (Fig. S3). O3
fluxes were in the same range of magnitude, typically between -20 and
0 nmol m-2 s-1, as those reported by previous studies at the
same site (Stella et al., 2013b, 2011b; Tuzet et al., 2011) and in the
literature over various canopies such as grassland (Stella et al., 2013a),
barley (Gerosa et al., 2004), potato field (Coyle et al., 2009) or forests
(Fares et al., 2010; Gerosa et al., 2005), although O3 flux magnitude is
sharply dependent on local O3 mixing ratio. We found similar magnitudes
of ozone fluxes in August and September as those reported by Stella et
al. (2013a) over a meadow during the summer. We also found similar nocturnal
O3 deposition velocity as found by Stella et al. (2011a) over bare soil
during summer, but with a higher daily maximum (0.8 cm s-1 instead of
0.5–0.6 cm s-1). Seasonal and daily dynamics of O3 deposition
velocity are shown in Fig. 5. We further find a similar midday magnitude as
Stella et al. (2011a) found in April with wetter soils. Night-time ozone
deposition velocity did not go lower than around 0.2 cm s-1 in our
study, as also found by Zhu et al. (2015) over a growing wheat in China,
Stella et al. (2011a) over bare soil in summer, and Lamaud et al. (2009) over
maize. These authors as well as Huang et al. (2016) clearly show that this is
due to non-stomatal deposition being primarily driven by u∗ which
does not reach zero at night during these periods. We can hence conclude that
we found consistent ozone deposition in August and September compared to
other studies at that site or in other geographical areas. When compared to
previous years at the same site the deposition velocity measured during the
winter in this study was clearly smaller. We interpret this as being
primarily due to u∗ being smaller that winter compared to other
winters, as well as due to a bad development of the winter crop due to soil
drought in September (SWC = 20 % in the 15 cm horizon).
Seasonal changes of ozone deposition velocity VdO3 and
NO fluxes. Blue lines show median and grey area inter-quantiles.
Comparison of ozone fluxes to the Stella et al. (2011a)
parameterisation over soil
In order to compare to previous studies of ozone deposition onto bare soil on
the same site, we have calculated the soil surface resistance as in Stella et
al. (2011a) and deduced the ozone deposition velocity as
VdO3 = (RsoilO3 + RbO3 + Ra(zref))-1.
In this way, we can compare the two studies while excluding any confounding
factors (roughness and turbulent exchange intensity). We can see in Fig. 6a
that the measured ozone deposition velocity during August follows the
parameterisation of Stella et al. (2011a) most of the time except for some
days including 18 and 19 August which correspond to slurry application and 24, 25, and 26 August, which
follow a small rainfall. We also
see an overestimation of the Stella parameterisation before the 18 August,
which we interpret as being due to the straw and wheat residues being present
on the ground before slurry incorporation. This comparison hence demonstrates
that the ozone deposition was indeed increased slightly following slurry
application and subsequently following rainfall. This may be either due to a
physical reason (increased surface exchange on the soil due to tillage or
humidity change due to slurry) or a chemical reason (surface reactivity
changes due to added organic matter or volatile organic compound (VOC)
emissions from the slurry). Figure 6b further shows that the main differences
are observed for wet soils and relatively low temperatures (this is after
rainfall) and to a lesser extent for drier and hotter situations (following
slurry spreading).
(a) Comparison of ozone deposition velocity from this study
(black dots), and from the parameterisation of Stella et al. (2011a) (red
line) based on surface temperature. (b) Response of ozone deposition
velocity to surface humidity RH(z0) and surface temperature T(z0).
Shown are data from this study and from the parameterisation of Stella et
al. (2011a). The period covered is from 14 August to 6 September which is
before and after slurry spreading and corresponds to Fig. S5.
(a) Diurnal cycles of global irradiance and net radiation,
air and soil temperatures, relative humidity and wetness index averaged over
the three periods of interest at the Grignon field site. The shaded areas
represent the interquartile range. (b) Diurnal cycles of NO,
NO2 and O3 mixing ratios and fluxes as well as the deposition
velocities of NO2 and O3, averaged over the three periods of
interest at the Grignon field site. The shaded areas represent the
interquartile range. The deposition velocity of NO2 and O3 based on
the fluxes accounting for chemical reactions above ground are also shown
(VdO3 and VdNO2 corrected).
Diurnal cycles of mixing ratios and fluxes over periods of
interest
O3 mixing ratios exhibited a typical diurnal cycle that was governed by
photochemistry and convective mixing within the boundary layer and from the
free troposphere during daytime. It started to increase with sunlight around
07:00, and declined in the evening starting from 18:00 due to
lack of photochemical formation in the absence of sunlight, as well as
deposition and destruction with NO in this high NOx emission area. In
general, NO mixing ratios featured a marked peak in the early morning and
remained high until around 13:00 UTC (Fig. 7b). During the early afternoon,
the O3 increase was correlated with the NO decrease. NO2 mixing
ratios showed a bi-modal diurnal cycle with its maxima in correspondence with
morning and evening traffic peaks, i.e. around 06:00 and 19:00.
The NO fluxes also showed a diurnal cycle similar to the one of soil
temperature with an emission peak around 00:00 (Fig. 7a and b). This
suggests that NO emissions are related to nitrification, for which the
emission rate is an exponential function of soil temperature (Henault et al.,
2005). This was already shown for the Grignon soil by Laville et al. (2011).
The fact that NO fluxes decrease earlier than soil temperature is most likely
due to titration of NO by O3 in the late morning and early afternoon,
causing the NO emissions at the reference height to be reduced with respect
to ground emissions. After correction for chemical reactions the NO emissions
diurnal cycle is indeed at a peak later in the day, more in phase with ground
temperature (see Fig. 11). This is also indicated by the positive NO2
flux observed during the same time of the day. The O3 flux was mainly
negative (deposition) and follows the diurnal dynamics of measured mixing
ratios. In terms of deposition velocity, the ozone deposition velocity
followed a clear diurnal cycle with a maximum during the day and a minimum at
night. The measured NO2 deposition velocity showed slightly negative
values, but slightly positive ones when corrected for reactions with NO and
O3.
Influence of organic and mineral fertilisations on NO emissions
The NO flux averaged over the whole period was 0.09 nmol m-2 s-1
(mean), which is in the range of previous findings for the same site.
Laville et al. (2011) and Loubet et al. (2011) reported yearly averaged NO fluxes
varying between 0.07 and 0.15 nmol m-2 s-1 for 2007–2009. The
NO flux distribution was shifted towards positive values after the organic
fertilisation in August (Fig. S3), with the mean NO flux during the 2 weeks
following the fertilisation (0.49 nmol m-2 s-1) being six times
larger than the one for the whole period. For the same period, the ozone flux
distribution was shifted towards more negative values. Figure S3 also shows
that flux distributions after mineral fertilisation do not differ much from
the ones relative to the whole period. During the 2 weeks following the
February mineral fertilisation the NO flux increased less and was only
1.7 larger than over the whole period (0.14 nmol m-2 s-1). These
numbers are also in line with those reported following fertilisation on the
same soil in the 2007–2009 period by Laville et al. (2011) and Loubet et
al. (2011), which also showed some periods with slightly negative NO fluxes.
Stella et al. (2012) measured a larger peak of NO emissions following slurry
spreading, but only lasting 2 to 3 days, which was probably due to a
drier soil in our study compared to Stella et al. (2012).
Following the slurry application, the NO emissions amounted to
0.1 kg N ha-1, which represents 0.24 % of the applied nitrogen
(42 kg N). Following the mineral fertilisation, the NO emissions amounted
to 0.02 kg N ha-1, which represents 0.037 % of the applied
nitrogen (54 kg N). Over the whole period from August 2012 to March 2013,
we evaluate a loss of 0.26 kg N ha-1. With a total N input of
96 kg N ha-1, this gives an estimate of the NO emission factor of
0.27 %, which is similar to values reported earlier for the same site
(Laville et al., 2011) but one order of magnitude larger than the EMEP/IPCC
default value of 0.04. Nevertheless, this is an average value calculated with
the Tier 1 approach, which does not take into account correction factors
depending on soil pH or fertiliser type. This more detailed approach, the
Tier 2, has not been developed for NO (EEA, 2016).
The reasons for lower emissions following winter mineral fertilisation than
following summer manure application are manifold. Even if the amount of
applied nitrogen was similar for the two cases (42 and 54 kg N ha-1),
meteorological and soil conditions were much more favourable for
nitrification in summer than in winter (Davidson, 1992; Williams and
Fehsenfeld, 1991). Indeed, NO emissions from agricultural soils are primarily
the by-products of nitrification, and this hypothesis was tested for the
Grignon site by Laville et al. (2011). Nitrification is inhibited by low soil
temperature and high water content that causes anoxia. Soil temperature was
much lower in February than in August (2.5 compared to 20 ∘C on
average). February was particularly humid, with a total precipitation of
10 mm, while in August no significant rain event occurred after the first
week. In this period indeed, the soil was only humidified by the organic
manure supply (on a 4.8 mm thick layer) that was applied on a dry soil. The
soil water content at 5 cm depth in September 2012 was around 21 % in
volume, while in February it was 33 % in volume. These two factors led to
more favourable conditions for nitrification in August than in February.
Meteorological variables and NOx–O3 mixing ratios and
fluxes measured during the period 14 to 29 August 2012 at the Grignon field
site. Ticks on the x axis correspond to midnight.
Influence of surrounding roads on the measured fluxes and
concentrations of the NO–NO2–O3 triad
Using the FIDES flux and concentration footprint model (Loubet et al., 2010)
we evaluated the footprint of nearby roads. Overall the flux footprint from
the nearby roads was smaller than 1 % (which means that only 1 % of
the road emissions contributes to the flux at the mast) most of the time, but
the concentration footprint reaches up to 10 % during some episodes, with
separate roads contributing differently depending on the period (Fig. S1).
Assuming a conservative emission of 250 mg km-1 vehicle-1 and an
average vehicle count of 10 000 vehicles day-1 (2010 counts,
“Statistiques du département des Yvelines pour 2010” ranges between
5000 and 15 000), we evaluate that the roads contribute from 4 to 40 %
to the measured fluxes. However, since vehicles emissions of NOx have a
sporadic nature, 10 000 vehicles day-1 means a maximum of ∼ 1
vehicle every 2 s (if we consider, conservatively, that most of the traffic
is condensed during 9 h only). These vehicles are also moving at about
90 km h-1 (25 m s-1), hence leading to a moving point source of
NOx. We therefore expect that the signal of this moving and sporadic
source is not captured by the EC method, and would be filtered out by
despiking and flux calculation procedures (Foken, 2008; Mahrt, 2010).
Chemical interactions: the NO–NO2–O3 triad and effect on
the fluxes
In order to investigate the interactions between the fluxes and mixing ratios
of the NO–NO2–O3 triad, we focus on the period from 14 to
29 August 2012, during which all fluxes were measured and NO fluxes were the
highest.
The 2 weeks following the organic manure application (from 18 to 19 August)
are characterised by hot sunny days, with maximal global radiation above
800 W m-2, except for 24 August when the only rain event occurred
(Fig. 8). The period of 18 to 23 August was the warmest, with soil surface
temperatures above 40 ∘C at noon during most days, while the air
temperature decreased from around 35 to around 20 ∘C during the same
period. The soil temperature at 5 cm depth followed the same trend, but with
a lower daily maximum and a higher night-time minimum. Due to sensor
breakdown the soil water content was not measured during this period. The
small latent heat flux (LE) after the 19 August, (17 W m-2 on average
between 19 and 31 August) the large sensible heat flux (60 W m-2 on
average) and radiation (212 W m-2 on average) indicate that the soil
humidity of the top soil layer was low. Hence, we assume that the SWC was
probably similar to what was measured in September (around 20 % in
volume), which is ideal for nitrification to occur (Laville et al., 2011;
Oswald et al., 2013).
The 18 August was the first day when NO emissions from the soil occurred. The
emissions lasted around 2 weeks following the organic fertilisation
(Fig. 4), during which the NO flux during daytime exceeded
0.5 nmol m-2 s-1, peaking around 00:00. The nocturnal NO
flux usually decreased to zero, except for the night of 25 August,
characterised by strong winds (Fig. 8). The maximum of the NO emissions was
2.7 nmol m-2 s-1 observed 6 days after fertilisation on
21 August.
Diurnal cycles of the O3 penetration depth in the soil
(ΔdryO3), the aerodynamic (Ra(zref)),
boundary layer (RbO3) and soil resistances
(RsoilO3) for O3, the chemical reaction time τchem and transport time τtrans, the chemical reaction
rates for NO2 photolysis JNO2 and NO depletion by O3
(kr×[O3]), and the Damköhler number
(Da), averaged over the periods of interest at the Grignon field
site. The shaded areas represent the interquartile range.
The NO2 flux daily pattern was different during the two weeks following
organic manure application compared to the period before (Fig. 8). It was in
general positive during the day and around zero at night during the period
from 18 to 29 August, except for the night of 25 August when it was large and
negative. Positive NO2 fluxes might be explained by chemical reactions
between NO and O3 in the surface layer (De Arellano et al., 1993), which
will be discussed in the next section.
The O3 flux was also significantly higher (Student t test p value
lower than 2×10-16) following organic fertilisation (mean
-10.7 nmol m-2 s-1) than during the rest of the experimental
campaign (mean -3.1 nmol m-2 s-1) (Fig. S3). Since the mixing
ratio of O3 was quite variable during the campaign (Fig. 4), it is
more interesting to look at the deposition velocity which underpins the
surface exchange processes (Figs. 7b and 8). The median VdO3
during the organic fertilisation event exceeded the median over the rest of
the experimental campaign by a factor of 2. However, this increase in
O3 deposition velocity cannot be explained by reaction with soil-emitted
NO alone as the O3 flux is an order of magnitude larger than the NO
flux.
Different pathways for the near-surface O3 removal are likely:
(i) photolysis of O3 by ultraviolet light in the presence of water vapour
forming OH radicals, (ii) gas phase reactions with reactive VOCs and
(iii) heterogeneous reactions with the soil or with molecules adsorbed on
soil.
The NO mixing ratio was well correlated with the NO flux, with a normal
correlation coefficient of 40 % for the two weeks following the organic
fertilisation (excluding 24–25 August), while it was only 2 % for the
7-month period. This suggests that, following fertilisation, the ambient NO
levels were mainly due to local emissions. The NO2 mixing ratio was less
correlated with the NO2 flux, suggesting that NO2 levels were more
related to advection from surrounding road traffic than from local emissions.
Indeed, both NO and NO2 are emitted from road traffic and urban
pollution, but the NO2 component quickly becomes prevalent as the plume
is advected, especially in the presence of high O3 levels, as in our case
(Carslaw, 2005; Minoura and Ito, 2010). The minimum night-time mixing ratio
is mainly controlled by night-time wind velocity: the higher the night-time
velocity, the higher the mixing ratio, due to a better mixing in the
atmospheric surface layer. During conditions with lower wind speed,
deposition and reaction with local NOx sources lead to a high depletion
of O3 during the night.
Half-hourly values of photo-stationary state ratio (PSS) and Q=kr[NO][O3] - JNO2[NO2] (s); chemistry and
transport timescales (τchem and τtrans) and Damköhler
number (Da); measured NO, NO2 and O3 fluxes and surface
fluxes as computed by assuming a logarithmic flux divergence profile
(FNO, FNO2 and FO3) at the Grignon field
site.
To what extent are the chemical reactions between NO, NO2 and
O3 modifying the fluxes above the ground?
Measured mixing ratios and fluxes of NO, NO2 and O3 are affected by
chemical reactions (Reactions SR1 to SR4 in the Supplement) in addition to
emissions and deposition processes. Especially, the diurnal fluxes of
NO2 observed from 18 to 23 August, were positive (emissions) and of the
same order of magnitude as the NO fluxes, while they were negative
afterwards. The simultaneous observation of positive NO and NO2 fluxes
are typical for the NO-to-NO2 transformation below the flux observation
level in the presence of high O3 mixing ratios. This phenomenon is
called “apparent NO2 emissions” and was observed in other studies
mainly above dense or tall canopies (Ammann et al., 2012; Min et al., 2014;
Plake et al., 2015). For the Reactions (SR1)–(SR2) to occur below the
measurement height, the turbulent transport time (τtrans) needs
to exceed the chemical reaction time (τchem) (Arellano and
Duynkerke, 1992; De Arellano et al., 1993; Lenschow and Delany, 1987; Plake
et al., 2015; Stella et al., 2011a, 2012, 2013a). The Damköhler number
Da=τtrans/τchem is often used to determine
the conditions favourable for chemical reactions: in cases when Da
is higher than unity chemical reactions are faster than the transport (flux
divergence), whereas Da values smaller than 0.1 indicate that the
influence of chemical reactions was negligible. The aerodynamic resistance
Ra(zref) (Eq. S8) was overall quite small and ranging
from 45 to 128 s m-1 (first and third quantiles), hence leading to a
quite short transport timescale (but larger than 100 s most of the time).
The boundary layer resistance was around 22 and 43 s m-1 (first and
third quantiles) for O3 (Fig. 9). The surface resistance for O3 was
estimated as
RsoilO3 = VdO3-1 - Ra(zref) - RbO3,
and dominated the other resistances (100 to 480 s m-1). The O3
penetration depth in the soil was estimated as the depth necessary to explain
the measured RsoilO3 if molecular diffusion in the soil pores
is the main limitation factor. In practice this corresponded to the dry soil
layer used in Personne et al. (2009). This depth ranged from 2 to 10 mm on
average and was smaller at noon than during the night (Fig. 9). Overall, the
chemical time τchem and the transport time τtrans
were of the same order of magnitude at any time of the day between
applications and during mineral fertilisation, and τchem was
smaller than τtrans during the organic fertilisation. As a
consequence, the Damköhler number was around unity most of the time and
larger than unity during the organic fertilisation period, showing that the
reaction between O3, NO and NO2 happened during transport from the
ground to the EC measurement height at all times at this site. During the
fertilisation event, the Damköhler number was especially high at night,
when the transport time increased more substantially than the chemical
timescale. These results are similar to findings by Stella et al. (2012) for
the same site over bare soil. During the periods with vegetation, the
increase of the transport timescale above the canopy was less than that of
the chemical timescale during night-time, as the presence of vegetation
increases the mixing, and, hence diminishes Ra(zref).
The Damköhler number shows that NO reacts with O3 and that
photolysis also plays a role. How does this affect the NO flux measured at
the reference height compared to the one at the ground? We quantified this
variation by numerically solving Eq. (S13), based on the model of Duyzer et
al. (1995). Due to the reaction with O3, the calculated NO flux at the
ground surface was on average 32 % larger than that at the measurement
height during the period 17–29 August (0.93 instead of
0.63 nmol m-2 s-1). This would represent an increase of 37 g of
N emission following slurry spreading. For NO2, the calculated flux at
the ground surface was mostly negative while it was mainly positive at the
reference height during the period 18–22 August. On average the NO2
flux at the ground was -0.33 nmol m-2 s-1 over the period
17–29 August while it was -0.03 nmol m-2 s-1 at the reference
height. For NO fluxes, the major discrepancy between fluxes at the surface
and the measurement height occurs during periods with relatively large and
stable values of the Damköhler number (Fig. 10), as this is the case when
chemical reactions consume NO before it reaches the measurement height.
The derivation of surface fluxes with the Duyzer model also leads to a
diurnal cycle of the NO flux that is closer to the one observed for ground
temperature, corroborating the hypothesis that ground emissions are mostly
due to nitrification for our site (Fig. 11).
Diurnal cycles of ground temperature, NO flux at measurement height
and at surface determined by the logarithmic profile in August 2012.
Since the O3 deposition flux was much larger than the NO flux, the
reaction with NO changed the absolute value by only 3 % when comparing
the flux at the measurement height to the ground surface. Indeed, as only
Reactions (SR1) and (SR2) are considered in Eqs. (S12) and (S13), which we
used to numerically evaluate surface fluxes, we obtain: ΔFNO=ΔFO3=-ΔFNO2=0.3 nmol m-2 s-1 where Δ
stands for the difference between surface and measurement height.
Why is O3 deposition increasing following organic
fertilisation?
We observed that following organic fertilisation (performed by injection and
hence soil tillage), O3 deposition increased by a factor of 2 (as
shown by the deposition velocity, Figs. 9 and 10). Several hypotheses may
explain this increase: (1) the increased surface exchange due to soil
tillage, (2) the reaction with NO emitted by the ground, and (3) the reaction
with VOCs emitted by the ground.
The first hypothesis is that the increase in deposition velocity following
the organic fertilisation could be due to a change in physical
characteristics of the soil surface. Indeed, the application of cattle slurry
with a trailing hose modifies the soil structure at the surface which
consequently increases the available surface for O3 deposition, and
therefore the deposition velocity. This hypothesis is consistent with the
comparison of measured deposition velocities and modelled deposition
velocities using the Stella et al. (2011a) RsoilO3
parameterisation (see Sect. 3.3.3 and Fig. 6a). Indeed, while there is a good
agreement between measured and modelled VdO3 after the
26 August (i.e., after the rainfall event), modelled VdO3
systematically underestimates measured Vd between slurry
application and the rainfall event. Since the parameterisation of
RsoilO3 was obtained for the Grignon site over different
periods, that means RsoilO3 accounts for the mean soil
structure of the Grignon site. Therefore, it can be hypothesised that
(i) Rsoil is underestimated from slurry application to the rainfall
event due to the change of soil surface structure, and (ii) after the
rainfall event, the soil surface recovers its mean structure corresponding to
the RsoilO3 parameterisation.
The second hypothesis is that O3 would react with NO emitted by
the soil. Although the reactions with NO during transport are shown to be
small compared to the NO flux (Fig. 10), reactions in the soil surface layer
may be more significant due to large NO concentrations in the soil, despite
the fact that this layer is very small. A graph of the difference between the
measured and the modelled ozone flux following fertilisation (Fig. S4) seems
to show that the additional O3 deposition is correlated with the NO
flux. This would mean that the NO2 produced in the soil by reaction with
NO would be adsorbed on the soil surface either in the mineral phase or
dissolved in the water phase as NO2. To evaluate this assumption
further, we evaluated the Damköhler number in the soil surface layer by
assuming that the layer depth is equal to the O3 penetration depth
δO3soil (Fig. 9). In this layer the transport time is
equal to soil resistance for O3 times the penetration depth
RsoilO3×δO3soil. We can evaluate the NO
mixing ratio that would explain the additional O3 destruction at the
surface, by searching for the value of [NO]soil that
satisfies τtrans(Soil, O3) = τchem(Soil,
O3). By doing so, we found that [NO]soil would need
to reach 5 to 40 ppm to explain the increase in O3 deposition following
organic fertilisation. Gut et al. (1998, 1999) measured NO mixing ratios at a
2 cm depth in the soil under wheat with the membrane tube technique and
report mixing ratios around 100 ppb and always below 400 ppb following
fertilisation, which is 1–2 orders of magnitude below the mixing ratio
which would be needed to explain the observed O3 flux. Moreover, the
rate of NO production in the soil surface layer would have to be equal to the
O3 flux to the ground (around 20 nmol m-2 s-1) which is an
order of magnitude larger than what Gut et al. (1998) or Laville et
al. (2009) report as maximum NO flux. However, we should stress that both Gut
et al. (1998) and Laville et al. (2009) report NO fluxes that were measured
in the presence of O3 and hence would have been depleted by reaction with
it in a similar way as here.
A third hypothesis is that O3 would react with VOCs emitted by the
ground. Reactive VOCs such as sesquiterpenes and monoterpenes have been previously
found to be emitted from soils (Horvath et al., 2012; Penuelas et al., 2014),
and some of these sesquiterpene species react with O3 in the order of a
few seconds. The reactions of O3 with larger terpenes are important
sources of OH, as well as the ozonolysis of simpler unsaturated compounds
(Donahue et al., 2005). Currently, there are few or no data available on
the emission of VOCs from slurry application. However, a recent study mainly
focusing on quantification of odour emissions from soil application of manure
slurry showed the formation of a certain number of VOCs, included organic
sulfur compounds, carboxylic acids, alcohols, carbonyl compounds (ketones and
aldehydes), aromatic compounds (phenols and indoles) and nitrogen compounds
(Feilberg et al., 2015). Based on their analyses, the compound most
responsible for the overall odour impact from the VOC emissions was
4-methylphenol. These authors also showed the emission of trimethylamine, a
compound that can react quickly with O3, leading to formation of
secondary organic aerosols (Murphy et al., 2007). Furthermore, these authors
suggest that a large part of these VOCs are formed through ozonation
reactions (i.e. byproducts of ozonation: methanol, acetone and
acetaldehyde). Indeed, the slurry would be transported downwards through the
soil, where efficient heterogeneous reactions can take place at particle
interfaces. It has been shown that the heterogeneous reaction probabilities
may be much greater than anticipated. For example, measurements on oxide
surfaces with a chemical structure commonly found in VOCs (i.e. alkenes,
terpenes, carbonyls) showed that the O3 reaction probability of a
surface-attached alkene can be up to 5 orders of magnitude greater than
for the same reaction in the gas phase (Stokes et al., 2008). In the same
way, Fick et al. (2005) observed that ozonolysis reaction rates of some
terpenes were much higher than predicted, possibly as a result of reactions
on the surfaces used in their experiments. These results suggest that
terpenes can remain on the surfaces, enhancing the O3 reactivity.
Similarly, some other authors observed that surface reaction probabilities
with O3 were 10 to 120 times greater than their corresponding gas-phase
values (Dubowski et al., 2004; Springs et al., 2011). It is also known that
soils can act as a sink of VOCs, by their adsorption to soil mineral particle
surfaces and humic substances (Penuelas et al., 2014). Hence, it is likely
that surface chemistry including photo-enhanced O3 uptake on organic
matter (Jammoul et al., 2008; Reeser et al., 2009) may explain the increase
in O3 deposition, a process not yet described in the literature. It may
also be likely that O3 is destroyed by very reactive VOCs in the gas
phase as hypothesised by Wolfe et al. (2011). These gas-phase reactions,
however, require that the chemical reaction time be shorter than the
turbulence transport time (Plake et al., 2015; Stella et al., 2012).
However, our study does not allow us to conclude definitively which of the
three hypotheses is the most likely.
Conclusions
Eddy covariance flux measurements of the NO–NO2–O3 triad during a
7-month period allowed evaluating several mechanisms controlling the
exchange of these reactive trace gases with an agricultural soil. The eddy
covariance technique proved to be suitable at capturing seasonal and diurnal
dynamics of the fluxes, and allowed us to interpret flux behaviour according to
meteorological variables, fertilisation practices and chemical reactions.
Nevertheless, random uncertainty was particularly important (> 20 %)
during morning traffic peaks due to the non-stationarity of NOx and O3
mixing ratios. As concerns NO2, uncertainty was even higher (up to
40 %) due to the indirect measurement method. We thus recommend caution
in the use of the method in non-stationary conditions, and combined
measurements of horizontal gradients of mixing ratios to quantify the effect
of advection. Also, additional measurements of surface mixing ratios would be
useful to check the reconstruction of surface fluxes that we performed by
using the logarithmic-profile model of Duyzer. Finally, high NO2 to NO
conversion efficiency should be assured to reduce uncertainty of NO2
fluxes.
In particular, the magnitude and temporal variability of NO emission fluxes
following two fertilisation episodes were analysed, one in summer and the
other one in winter. Mean NO emissions during the whole period were in
agreement with previous studies on the same site. Emissions were
significantly higher (Student t test p value lower than 2×10-16, and a factor of 7 difference on the mean) during 2 weeks
following organic fertilisation in August than during the rest of the
experimental period. These large emissions are mainly due to favourable
conditions for nitrification: soil water content around 20 % and high
temperatures. In February, following mineral fertilisation, the increase of
NO emissions was less pronounced, although the same amount of N was applied.
This difference is likely due to less favourable conditions for nitrification
in February (low temperature and higher soil water content), rather than to
the different form of fertiliser. On average over the whole period, we
derived a loss of 0.26 kg N ha-1 as NO from the field. With a total N
input of 96 kg N ha-1, this results in an NO emission factor of
0.27 %, which is in the lower range of earlier reported values on this
site (Laville et al., 2011).
Our findings show that NO emissions from agricultural soils are limited
(0.27 % of the N–NO applied over the 7-month period, which with a
conservative estimation can be extended to a yearly amount). When
hypothetically extended to France with an averaged nitrogen fertiliser use of 80 kg N ha-1 over a
fertilised area of around 26 Mha, this would lead to a total emission of
NOx of around 5.6 kt N–NO. This is negligible compared to national
emissions which are around 240 kt N–NO (CITEPA, 2015). The seasonality and
spatial distribution of these emissions may, however, lead to air quality
issues during spring and late summer-autumn which are the main fertiliser
application periods in rural environments. Indeed, most of the emissions we
measured occurred within a few weeks following fertilisation. In terms of
ozone, our findings are in accordance with previous ones, showing that ozone
is efficiently deposited throughout the year. This means that crops are
participating through this process in the reduction of the atmospheric
oxidising capacity.
The O3 deposition velocity was significantly higher following organic
fertilisation than during the rest of the experiment (Student t test
p value lower than 2×10-16 and a factor 3 difference on the
mean), despite the fact that vegetation was absent. This increase in O3
deposition could not be explained by the reaction of O3 with NO in the
atmosphere as the NO flux was an order of magnitude smaller than that of
O3. The process behind this ozone deposition increase remains to be
discovered. We hypothesised three underlying processes: (1) increase in soil
surface due to soil tillage, (2) reaction with NO in the soil layer and
(3) reactions of O3 with VOCs emitted by the slurry. None of these
hypotheses can be dismissed and further investigation is required.
Experiments in controlled conditions are desirable to better understand these
processes.
The evaluation of the chemical and turbulent transport times showed that
reactions between NO, NO2 and O3 below the measurement height
occurred during the whole measurement period, leading to a depletion of NO
and a build-up of NO2 from the ground to the measurement height.
Following organic manure application, NO fluxes were reduced by 30 % from
the surface to measurement height, while the NO2 fluxes switched from
deposition to uptake, being negative at the surface and positive at the
measurement height. This phenomenon of “apparent NO2 emissions” was
reported in other studies, especially above forests. Here it also appears to
be important above a bare soil and at moderate measurement heights, during
conditions of strong NO emissions and high ambient O3 mixing
ratios.