Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, ...greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.
We assessed the compliance of a Dutch landscape, dominated by dairy farming, with environmental quality standards using a combination of model calculations and measurements. The total ammonia ...emission of 2.4 kton NH
3 yr
−1 does not exceed the environmental quality standard (2.6 kton NH
3 yr
−1). Nevertheless, the total N deposition (on average 24.4 kg N ha
−1 yr
−1) is such that critical N loads are exceeded at 53% of the nature areas. The deposited N mainly results from non-agricultural sources and agricultural sources outside the area (72%). The calculated average NO
3
− concentration in the upper groundwater does not exceed the 50 mg l
−1 threshold. Calculated annual average N-total and P-total concentrations in discharge water are relatively high but these cannot be directly compared with thresholds for surface water. The results suggest that compliance monitoring at the landscape scale needs to include source indicators and cannot be based on state indicators alone.
► There is scope for environmental monitoring programs at the landscape scale. ► Landscape assessment of state indicators for N and P require models and measurements. ► Monitoring at the landscape scale needs to consider farm management indicators.
The compliance of an agricultural landscape with quality standards is investigated using a combination of model calculations and measurements.
The integrated modelling system INITIATOR was applied to a landscape in the northern part of the Netherlands to assess current nitrogen fluxes to air and water and the impact of various agricultural ...measures on these fluxes, using spatially explicit input data on animal numbers, land use, agricultural management, meteorology and soil. Average model results on NH
3 deposition and N concentrations in surface water appear to be comparable to observations, but the deviation can be large at local scale, despite the use of high resolution data. Evaluated measures include: air scrubbers reducing NH
3 emissions from poultry and pig housing systems, low protein feeding, reduced fertilizer amounts and low-emission stables for cattle. Low protein feeding and restrictive fertilizer application had the largest effect on both N inputs and N losses, resulting in N deposition reductions on Natura 2000 sites of 10% and 12%, respectively.
► We model nitrogen fluxes and the impact of agricultural measures in a rural landscape. ► Average model results appear to be comparable to observations. ► The measures low protein feeding and restrictive fertilizer application had the largest effect.
Effects of agricultural management on N losses to air and water are evaluated at landscape scale combining a model assessment and measurements.
We present a novel high-resolution inverse modelling system (“FLEXVAR”) based on FLEXPART-COSMO back trajectories driven by COSMO meteorological fields at 7km×7km resolution over the European COSMO-7 ...domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions (“baselines”) consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH4 emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter (“FLExKF”) system and with TM5-4DVAR inversions at 1∘×1∘ resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7km×7km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at 1∘×1∘. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.
Ammonia deposition is a threat to many natural ecosystems, including coastal dune areas, because of eutrophication and acidification. Direct measurements of ammonia fluxes are nevertheless scarce. In ...this paper we present a full year of measurements to derive the ammonia dry deposition flux in a Dutch coastal dune ecosystem, based on the aerodynamic flux-gradient method (AGM). We found a mean ammonia flux of −7.1 ± 1.7 ng m−2 s−1, and an annual ammonia deposition flux of −132 ± 32 mol ha−1 yr−1 (equivalent to 1.8 ± 0.4 kg N ha−1 yr−1), which is at the low end of the range from estimates from literature made with inferential methods. Modeling the fluxes with the DEPAC module resulted in a mean flux of −17.0 ng m−2 s−1. The model overestimated the deposition fluxes, but diurnal variations of the fluxes derived from measurements were well captured by the model. We propose to change certain DEPAC parameters, like the leaf area index, to values more applicable for a dune ecosystem and show that this improves the agreement between model and measurements.
•Dry deposition fluxes of ammonia were measured in a Dutch coastal dune area.•Half-hourly data were collected for a full year with a wet denuder instrument.•Fluxes from the aerodynamic flux-gradient method were compared with modeling.•Modeled fluxes captured measured diurnal variations, but overestimated deposition.•Modeled fluxes were sensitive to leaf area index and compensation points.
Dry deposition of ammonia (NH3) is the largest
contributor to the nitrogen deposition from the atmosphere to soil and
vegetation in the Netherlands, causing eutrophication and loss of
biodiversity; ...however, data sets of NH3 fluxes are sparse and in general
have monthly resolution at best. An important reason for this is that
measurement of the NH3 flux under dry conditions is notoriously
difficult. There is no technique that can be considered as the gold
standard for these measurements, which complicates the testing of new
techniques. Here, we present the results of an intercomparison of two novel
measurement set-ups aimed at measuring dry deposition of NH3 at
half hourly resolution. Over a 5-week period, we operated two novel optical
open-path techniques side by side at the Ruisdael station in Cabauw, the
Netherlands: the RIVM-miniDOAS 2.2D using the aerodynamic gradient
technique, and the commercial Healthy Photon HT8700E using the eddy
covariance technique. These instruments are widely different in their
measurement principle and approach to derive deposition values from measured
concentrations; however, both techniques showed very similar results (r=0.87)
and small differences in cumulative fluxes (∼ 10 %) as long
as the upwind terrain was homogeneous and free of nearby obstacles. The
observed fluxes varied from ∼ −80 to ∼ +140 ng NH3 m−2 s−1. Both the absolute flux values and the temporal
patterns were highly similar, which substantiates that both instruments were
able to measure NH3 fluxes at high temporal resolution. However, for
wind directions with obstacles nearby, the correlations between the two
techniques were weaker. The uptime of the miniDOAS system reached 100 %
once operational, but regular intercalibration of the system was applied in
this campaign (35 % of the 7-week uptime). Conversely, the HT8700E did not
measure during and shortly after rain, and the coating of its mirrors
tended to degrade (21 % data loss during the 5-week uptime). In addition,
the NH3 concentrations measured by the HT8700E proved sensitive to air
temperature, causing substantial differences (range: −15 to +6 µg m−3) between the two systems. To conclude, the miniDOAS system appears
ready for long-term hands-off monitoring. The current HT8700E system, on the
other hand, had a limited stand-alone operational time under the prevailing
weather conditions. However, under relatively dry and low-dust conditions,
the system can provide sound results, opening good prospects for future
versions, also for monitoring applications. The new high temporal resolution
data from these instruments can facilitate the study of processes behind
NH3 dry deposition, allowing an improved understanding of these
processes and better parameterisation in chemical transport models.
During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO 2) ...exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO 2 seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO 2 gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO 2 cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO 2 due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO 2 transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO 2 uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO 2 anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO 2 anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO
2
) ...exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO
2
seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO
2
gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO
2
cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO
2
due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO
2
transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO
2
uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO
2
anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO
2
anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018.
This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
Oxidation of organic matter in peat above the phreatic groundwater table causes subsidence and carbon dioxide (CO2) emissions. Because 25 % of the Netherlands has shallow peat layers in its ...subsurface, it is essential for Dutch policy makers and stakeholders to have reliable information on present day and near future CO2 emissions under changes in groundwater levels. Furthermore, it is important to reduce greenhouse gas emissions in view of international agreements.We are developing GreenhousePeat: a nationwide model that synthesizes information on peat organic carbon content, land subsidence, and CO2 emission monitoring to model present-day and future CO2 emissions from subsiding peatlands.Here, we discuss the approach and input data of GreenhousePeat. GreenhousePeat is based on a UNFCCC approved model to predict CO2 emissions, albeit based on new input data: 3-D organic matter maps, nationwide subsidence rates, and ranges in oxidation fraction. We validate model outcomes with previously documented CO2 emissions measured at four different locations. We found that for one site the upper bound of the model reproduces the measured CO2 emissions. The modelled emissions at two sites have a relative deviation of approximately 73 % to 29 % from the measured emissions. Whereas one site is a net CO2 sink, although low emissions were modelled. Finally, we conclude on the suitability of the model for CO2 emission forecasting and suggest improvements by incorporating groundwater level information and land use type.
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