# Comparing bottom-up and top-down approaches at the landscape scale, including agricultural activities and water systems, at the Roskilde Fjord, Denmark

Emeline Lequy, Andreas Ibrom, Per Ambus, Raia Silvia Massad, Stiig Markager, Eero Asmala, Benoit Gabrielle, Benjamin Loubet

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## To cite this version:

Emeline Lequy, Andreas Ibrom, Per Ambus, Raia Silvia Massad, Stiig Markager, et al.. Comparing bottom-up and top-down approaches at the landscape scale, including agricultural activities and water systems, at the Roskilde Fjord, Denmark. EGU 2015, European Geosciences Union General Assembly, Apr 2015, Vienne, Austria. hal-01228845

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Submitted on 3 Jun 2020

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INRA
SCIENCE & IMPACT

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INGOS
Integrated non-CO2 Greenhouse gas Observing System

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# Comparing bottom-up and top-down approaches at the landscape scale, including agricultural activities and water systems, at the Roskilde Fjord, Denmark

Emeline Lequy, Andreas Ibrom, Per Ambus, Raia-Silvia Massad, Stiig Markager, Eero Asmala, Josette Garnier, Benoit Gabrielle, and Benjamin Loubet

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DTU

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cnrs
# Comparing bottom-up and top-down approaches at the landscape scale, including agricultural activities and water systems, at the Roskilde Fjord, Denmark

Emeline Lequy (1), Andreas Ibrom (2), Per Ambus (2), Raia-Silvia Massad (1), Stiig Markager (3), Eero Asmala (3), Josette Garnier (4), Benoit Gabrielle (1), and Benjamin Loubet (1)

(1) INRA, UMR1091 INRA-AgroParisTech Ecosys, F-78850 Thiverval-Grignon, France (emeline.lequy@grignon.inra.fr), (2) Tech Univ Denmark, Dept Chem & Biochem Engn, Ctr Ecosyst & Environm Sustainabil, DK-4000 Roskilde, Denmark, (3) Aarhus Univ, Dept Biosci, DK-4000 Roskilde, Denmark, (4) Univ Paris 06, CNRS, UMR Sisyphe 7619, F-75005 Paris, France

The greenhouse gas nitrous oxide (N2O) mainly originates in direct emissions from agricultural soils due to microbial reactions stimulated by the use of nitrogen fertilisers. Indirect N2O emissions from water systems due to nitrogen leaching and deposition from crop fields range between 26 and 37% of direct agricultural emissions, indicating their potential importance and uncertainty (Reay et al. 2012). The study presented here couples a top-down approach with eddy covariance (EC) and a bottom-up approach using different models and measurements. A QCL sensor at 96-m height on a tall tower measures the emissions of N2O from 1100 ha of crop fields and from the south part of the Roskilde fjord, in a 5-km radius area around the tall tower at Roskilde, Denmark. The bottom-up approach includes ecosystem modelling with CERES-EGC for the crops and PaSIM for the grasslands, and the N2O fluxes from the Roskilde fjord are derived from N2O sea water concentration measurements.

EC measurements are now available from July to December 2014, and indicate a magnitude of the emissions from the crop fields around 0.2 mg N2O-N m-2 day-1 (range -9 to 5) which is consistent with the CERES-EGC simulations and calculations using IPCC emission factors. N2O fluxes from the Roskilde fjord in May and July indicated quite constant N2O concentrations around 0.1 µg N L-1 despite variations of nitrate and ammonium in the fjord. The calculated fluxes from these concentrations and the tall tower measurements consistently ranged between -7 and 6 mg N2O-N m-2 day-1. The study site also contains a waste water treatment plant, whose direct emissions will be measured in early 2015 using a dynamic plume tracer dispersion method (Mønster et al. 2014). A refined source attribution methodology together with more measurements and simulations of the N2O fluxes from the different land uses in this study site will provide a clearer view of the dynamics and budgets of N2O at the regional scale. The complementarity between these bottom-up and top-down approaches and their usefulness to disentangle direct and indirect N2O fluxes will also be discussed.

## Acknowledgements:

This work was funded by the EU-FP7 InGOS project.

## References:

Mønster JG, Samuelsson J, Kjeldsen P, Rella CW, Scheutz C. Quantifying methane emission from fugitive sources by combining tracer release and downwind measurements – A sensitivity analysis based on multiple field surveys. Waste Management. 2014 Aug;34(8):1416–28.

Reay DS, Davidson EA, Smith KA, Smith P, Melillo JM, Dentener F, et al. Global agriculture and nitrous oxide emissions. Nature Clim Change. 2012 Jun;2(6):410–6.
# Context and objectives of the study

## The Roskilde region: an interfacial study site

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**Study site:**

- tall tower at the DTU Risø Campus (sensor at 96 m high)

- 5 km around the tall tower (80 km²)

**Features included here:**

- **large agriculture area** (crops: 18 km²)

- **inner Roskilde fjord** (36 km²)

- urban area (Roskilde and other smaller cities nearby)

- woody areas

→ Opportunity to study:

- **direct** emissions: crop fields & N fertilisers + microbial reactions

- **indirect** emissions: from NO₃⁻ leaching to freshwater bodies & estuaries + microbial reactions → **26-37%** of direct emissions: importance & uncertainty (Reay et al., 2012)

## Objectives of the study

- Compare the results of the **bottom-up and top-down** approaches both for the agricultural and the fjord areas

- Estimate the **distribution** between direct N₂O emissions and indirect emissions

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# Material and methods

## ❖ Bottom-up approach (terrestrial part)

- Distribution of crop fields and grasslands in the study site

- Use of two ecosystem models: Ceres-EGC and Pasim for crop fields and grasslands

- General functioning of the two models

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# Material and methods

## ❖ Bottom-up approach (terrestrial part)

- Distribution of crop fields and grasslands in the study site

- Use of two ecosystem models: Ceres-EGC and Pasim for crop fields and grasslands

- General functioning of the two models

From Ceres-Maize (Jones and Kiniry, 1986; Gabrielle et al., 2006)
Pasim (Calanca et al. 2007)

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# Material and methods

## ❖ Bottom-up approach (aquatic part)

- Roskilde fjord: mildly salty (10-15), shallow (3m) and recovering from eutrophication

- Measurements of N₂O concentrations in 15 points distributed in the Roskilde fjord

- Empirical equations to obtain the N₂O fluxes (transfer water → atmosphere function of wind speed, and [N₂O]eq depending on salinity and temperature)

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$$ \mathrm{FN_2O} = k_w * (C_w - C_e) $$

$K_w$ (m s⁻¹): gas transfer coefficient, f(u, 10m)

$C_a$ (g N₂O-N L⁻¹): equilibrium N₂O concentration in seawater, f(T, salinity, [N₂O]atm)

Bange et al. (2001), Weiss and Price (1980)

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# Material and methods

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## Top-down methodology: measurements and comparison to the bottom-up results

- tall tower equipped with inlet and anemometer at 96m high, tube-connected to a N₂O sensor (cf Ibrom et al. in this session)

- GIS: rasters of the agricultural area and the Roskilde fjord for which bottom-up results are available

- Source attribution within the rasters calculated according to Neftel et al. (2008) based on the model footprint of Kormann and Meixner (2001)

- Comparison: daily averages within the pixels of the rasters for the modelled and measured fluxes, compared at daily scale for the whole area and within each pixel of the raster.

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Raster of
the Roskilde
fjord

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Raster of
the
agricultural
area
# Results – terrestrial part

## ❖ Bottom-up results: CERES and PASIM simulations

* Very different annual fluxes from a plot to another

→ <1 to 10 kg N₂O-N ha⁻¹ year⁻¹

→ Due to the different level of fertilizers used in the plots (from unfertilized to >300 kgN ha⁻¹ yr⁻¹)

* Differences within the year between CERES and PASIM

→ Dates of fertilization

→ Dates of harvest / cutting

→ Quite heterogeneous emissions both at spatial and temporal scales

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# Results – terrestrial part

## ❖ Comparison with flux tower measurements

* Source attribution over the raster: max range=0-11%, median=3% of the total flux by pixel

* Comparison at daily scale

* ✓ Expected values of the models vs. overall measurements of the tower

* ✓ Linear regression: slope=0.4, R²=0.37

* → Not that bad, esp. for N₂O and suggests the tower underestimates the fluxes at landscape scale

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* Comparison between the pixels of the raster

* ■ Good agreement as well

* → **Slope of 0.7** between tower/models at the pixel scale (R²=0.65)

* → Very encouraging fit that suggest towers are able to detect “hotspots” in a heterogeneous terrestrial system (pixel size: 500x500m)

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# Results – aquatic part

## ❖ Bottom-up results: N₂O fluxes from water sampling

* Measurements once in May and July: very low concentrations of N₂O (<0.2 µg N₂O-N/L)

* Estimated fluxes can be positive or negative

* Area includes potentially high fluxes

* → Theoretically as high as those from agricultural area (10 µg N₂O-N m⁻² hour⁻¹)

* → Fluxes in July are lesser than those in May and mainly negative

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# Results – aquatic part

## ❖ Comparison with top-down approach

- Most of source attribution in the southwestern part of the tower (higher source attribution than the agricultural part: max range=0-20%, median=7%)

- Negative fluxes in both approaches, magnitude seems similar for the values in early July

- Waiting for coming data to complete this comparison from July to September

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## ❖ Comparison with agricultural fluxes:

- Per m², the Roskilde fjord emitted ~3-time less N₂O than the agricultural area

- Negative correlation between fluxes from water and agricultural areas (-0.5)

- Ratio of the agricultural and fjord emissions (daily averages): 77/23% to be confirmed by the bottom-up approach

N2O fluxes (g/m²/day)

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# Limits of the study

## ❖ Terrestrial part:

- Only the Jul-Dec part of 2014 so we missed the large flux induced by fertilizers

- Homogeneous input files may not depict thoroughly the real management in the agricultural plots

- Ceres-EGC is not suitable for other crops present in the study site (oat, potatoes...)

## ❖ Aquatic part:

- Still waiting for data to complete our database from May to Sept. 2014 and obtain a large overlap with the tall tower measurements

- No use of intermediary measurements (floating chamber, small tower...) at the Roskilde fjord as the equations are subject of large uncertainty

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# Conclusions and perspectives

## ❖ Good agreements:

- Fit between daily measurements and model outputs at daily scale over the whole agricultural area and in most of the pixels of the raster made from the agricultural area → 1D models without lateral transfers can predict good emissions with a good spatial accuracy at the landscape scale

- Encouraging results for the aquatic part: similar magnitudes, positive (emission) and negative (absorption) fluxes over the 15 points of the Roskilde fjord/raster

## ❖ Bottom-up and top-down approaches produce very similar trends and budgets at least for the study period at the landscape scale: here we show that the ratio between direct/indirect emissions (as defined in introduction) was ~77/23%, but we need to pursue the study to obtain one-year of tower measurements

## ❖ Next steps?

- Use of dedicated landscape model to compare with tower fluxes? Landscape-DNDC or integrative NitroScape (coming soon)

- Include other land uses such as urban systems, forests and so on

- Test this methods at the landscape scale for other tall towers in Europe?

- Possibility to feed the IPCC database with local/landscape emission factors

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Thank you for your attention!

View of the agricultural area and the Roskilde fjord from the tall tower

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Courteously from Ebba Dellwik, DTU

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