Agricultural Nitrogen Research Articles

Spatiotemporal distribution and controlling factors on ammonium in waters in the central Yangtze River Basin, China

High levels of ammonium in water can compromise the ecological environment and be harmful to human beings. It is of great significance to understand the source and controlling factors of ammonium in waters. However, the distribution and controlling factors on ammonium in the central Yangtze River Basin have been rarely reported. The results showed that 6.58% of the surface water (SW) exceeded the China national guideline of category III for NH4+-N (i.e., 1.0 mg/L) and 30.19% of the groundwater (GW) exceeded the China national guideline of category III for NH4+-N (i.e., 0.5 mg/L). Notably, the ammonium concentrations of the plain area in the middle were much higher, which reached to the highest value at the junction of the Yangtze River and Dongting Lake. Nitrogen in SW may originate from manure but more nitrogen sources in GW. The net anthropogenic nitrogen input (NANI) can provide enough organic nitrogen for the mineralization. NH4+-N in SW was more affected by fertilizer nitrogen and feed nitrogen input but more affected by agricultural nitrogen fixation in GW. Agricultural and industrial activities controlled NH4+-N in SW and GW by increasing nitrogen input and changing hydrological conditions. In general, this research exposed the controlling of different types of factors on ammonium in waters, providing a guidance for the water pollution prevention in study area.

Tree-Structured Parzan Estimator–Machine Learning–Ordinary Kriging: An Integration Method for Soil Ammonia Spatial Prediction in the Typical Cropland of Chinese Yellow River Delta with Sentinel-2 Remote Sensing Image and Air Quality Data

Spatial prediction of soil ammonia (NH3) plays an important role in monitoring climate warming and soil ecological health. However, traditional machine learning (ML) models do not consider optimal parameter selection and spatial autocorrelation. Here, we present an integration method (tree-structured Parzen estimator–machine learning–ordinary kriging (TPE–ML–OK)) to predict spatial variability of soil NH3 from Sentinel-2 remote sensing image and air quality data. In TPE–ML–OK, we designed the TPE search algorithm, which encourages gradient boosting decision tree (GBDT), random forest (RF), and extreme gradient boosting (XGB) models to pay more attention to the optimal hyperparameters’ high-possibility range, and then the residual ordinary kriging model is used to further improve the prediction accuracy of soil NH3 flux. We found a weak linear correlation between soil NH3 flux and environmental variables using scatter matrix correlation analysis. The optimal hyperparameters from the TPE search algorithm existed in the densest iteration region, and the TPE–XGB–OK method exhibited the highest predicted accuracy (R2 = 85.97%) for soil NH3 flux in comparison with other models. The spatial mapping results based on TPE–ML–OK methods showed that the high fluxes of soil NH3 were concentrated in the central and northeast areas, which may be influenced by rivers or soil water. The analysis result of the SHapley additive explanation (SHAP) algorithm found that the variables with the highest contribution to soil NH3 were O3, SO2, PM10, CO, and NDWI. The above results demonstrate the powerful linear–nonlinear interpretation ability between soil NH3 and environmental variables using the integration method, which can reduce the impact on agricultural nitrogen deposition and regional air quality.

The influences of graphene oxide and nitrification inhibitor on vegetable growths and soil and endophytic bacterial communities: Double-edge sword effects and nitrate risk controls

Crop yield and quality are substantial indicators of evaluating agricultural nitrogen management practices, and the nitrate (NO3−-N) is one of the predominant factors affecting crop quality. The NO3−-N accumulation in vegetable crop affects plant growth and quality and human health. Therefore, it is necessary to stimulate vegetable yield but eliminate excessive NO3−-N in soils and plants with feasible management strategies. Graphene oxide (GO) is a novel carbon nanomaterial that has attracted great attention, but rare research has been conducted to quantify the effects of GO on plant NO3−-N accumulation and microbial communities. This study explored effects of the GO and nitrification inhibitors, dicyandiamide (DCD) and 3, 4-dimethylpyrazole phosphate (DMPP), on vegetable yields and NO3−-N contents and bacterial communities in soil-cabbage (Brassica rapa subsp. Chinensis) system. The soil NO3−-N content was significantly reduced with the single GO application. The cabbage NO3−-N content was increased by 60.4 % while the cabbage yield was significantly enhanced by 101.9 % with the single GO application. Meanwhile, the Invsimpson index of soil bacterial community and the ACE and Chao1 richness estimators of endophytic bacterial community were significantly decreased by the GO application. Cabbage NO3−-N content was significantly and negatively correlated with the soil Myxococcota, endophytic bacterial community co-occurrence network edge, cabbage soluble sugar and cabbage proline. The GO application generated double-edged sword effects of positively promoting yield but causing risks of NO3−-N accumulation and quality deterioration. However, these adverse effects could be mitigated by the extra nitrification inhibitor application. The potential ecological risks of GO application to the vegetable quality and endophytic community should be considered.

N2O Emissions from Aquatic Ecosystems: A Review

Emissions of nitrous oxide (N2O) from aquatic ecosystems are on the rise due to the dramatic increase in global reactive nitrogen input by anthropogenic activities (e.g., agricultural nitrogen fertilizer use). However, uncertainties exist in the estimation of aquatic N2O budgets due to limited knowledge of mechanisms involved in aquatic N2O emissions, as well as the N2O flux measurements and modelling. To give a full picture of aquatic N2O emissions, this review discusses the biotic and abiotic mechanisms involved in aquatic N2O emissions, common methods used in aquatic N2O flux measurements (including field measurement methods and formula simulation methods), and alternatives for aquatic N2O budget estimation. In addition, this review also suggests that stable isotope technology is promising in the application of aquatic N2O source partitioning.

Towards Less Agricultural Nitrogen Use in China: Perspective from a Multi-Crop and Multi-Region Partial Equilibrium Analysis

Towards Less Agricultural Nitrogen Use in China: Perspective from a Multi-Crop and Multi-Region Partial Equilibrium Analysis

Characteristics of Nitrogen in Overlying Water and Sediment of Typical Agricultural Drainage Ditches during Different Periods in a Freezing-Thaw Area of China

In the Sanjiang Plain, agricultural drainage ditches effectively alleviate agricultural non-point source nitrogen pollution. However, limited information is known about the characteristics of bidirectional trans-ports of nitrogen between sediment and overlying and pore water in different patterns of ditches undergoing seasonal freezing-thawing cycles. It is vital to better understand nitrogen interception and purification by ecological ditches. In order to clarify the interception of ecological ditches on internal and external nitrogen, overlying water and sediment samples of two typical agricultural ditches were collected and analyzed in Sanjiang Plain during the growing seasons of 2015–2017. The results indicated that the N-NO3− in overlying water, which was higher than N-NH4+, was the dominant inorganic nitrogen, whilst, in the sediment, N-NH4+ was much higher than N-NO3−, which should be attributed to the soil’s adsorption of N-NH4+. In contrast to the dryland ditch, the paddy ditch had a more significant amount of inorganic nitrogen both in overlying water and sediment, which means that the non-point source nitrogen pollution caused by paddy fields was more severe than that of drylands. Compared with dryland ditches, N-NH4+ in the sediment of pad ditches seemed to be much easier to migrate to a deeper layer, which may cause a greater risk of nitrogen pollution to groundwater. Both in the overlying water and the sediment of ditches, nitrogen content fluctuated during different periods, and inter-annual variation was noticeable, which results means that estimation or prediction of the non-point source pollution output needs to extend the monitoring period and increase sampling frequency to reduce the great uncertainty. The findings may provide a foundation for forecasting agricultural nitrogen pollution and guide best management practices (BMPs) of non-point source nitrogen pollution control in seasonally frozen areas.

Halving mineral nitrogen use in European agriculture: Insights from multi‐scale land‐use models

AbstractThis paper explores the effects of a public policy that reduces by 50% the use of mineral nitrogen in European agriculture. Our results show that, for the European Union, halving mineral fertilizer use leads to: a decrease in agricultural production, a substantial increase in nitrogen use efficiency, lower use of organic fertilizer and a loss of agricultural competitiveness. At the global level, it leads to greater nitrogen consumption if no measure is taken on the demand side. Ultimately, our research highlights the critical importance of supply side adjustments, particularly in terms of cropland area expansion.

Plasma Agricultural Nitrogen Fixation Using Clean Energies: New Attempt of Promoting PV Absorption in Rural Areas

Plasma Agricultural Nitrogen Fixation Using Clean Energies: New Attempt of Promoting PV Absorption in Rural Areas

The problem of nitrogen in modern agriculture

Optimal nitrogen supply to plants, in conditions of sufficient moisture, allows for high crop productivity with high-quality indicators. The aim of this article was to summarize and analyze statistical data on the dynamics of nitrogen input and expenditure from arable land worldwide and in Ukraine, as well as provide practical recommendations for addressing the nitrogen issue in modern agriculture. The research utilized theoretical generalization, comparative analysis, graphical, abstract-logical methods and statistical data from FAOSTAT for the period of 2000-2020. The research results have shown that nitrogen input from mineral fertilizers has been constantly increasing both globally and in Ukraine. In contrast to global indicators, there has been a significant reduction in nitrogen input from manure in Ukraine, as well as a decrease in nitrogen input from atmospheric precipitation and through biological fixation by leguminous crops. The components of nitrogen balance, such as leaching, evaporation, and denitrification, play a significant role in nitrogen expenditure. These expenditure components tend to increase both globally and in Ukraine. The largest share in the expenditure component of all countries worldwide, including Ukraine, is occupied by nitrogen removal by cultivated crops. Calculations showed that the nitrogen balance on arable land, both globally and in most countries across different continents for the researched period, was positive. However, in Ukraine, it was negative for 18 out of 21 years. To solve this problem, practical recommendations are proposed using the best practices and developments of economically developed countries worldwide

Smart Farming Revolution: Portable and Real-Time Soil Nitrogen and Phosphorus Monitoring for Sustainable Agriculture.

Precision agriculture is crucial for ensuring food security in a growing global population. Nutrients, their presence, concentration, and effectiveness, are key components in data-driven agriculture. Assessing macro and micro-nutrients, as well as factors such as water and pH, helps determine soil fertility, which is vital for supporting healthy plant growth and high crop yields. Insufficient soil nutrient assessment during continuous cropping can threaten long-term agricultural viability. Soil nutrients need to be measured and replenished after each harvest for optimal yield. However, existing soil testing procedures are expensive and time-consuming. The proposed research aims to assess soil nutrient levels, specifically nitrogen and phosphorus concentrations, to provide critical information and guidance on restoring optimal soil fertility. In this research, a novel chip-level colorimeter is fabricated to detect the N and P elements of soil onto a handheld colorimeter or spectrophotometer. Chemical reaction with soil solution generates color in the presence of nutrients, which are then quantitatively measured using sensors. The test samples are collected from various farmlands, and the results are validated with laboratory analysis of samples using spectrophotometers used in laboratories. ANOVA test has been performed in which F value > 1 in our study indicates statistically significant differences between the group means. The alternate hypothesis, which proposes the presence of significant differences between the groups, is supported by the data. The device created in this paper has crucial potential in terms of environmental and biological applications.

Optimization of Nitrogen Fertilizer Management in the Yellow River Irrigation Area Based on the Root Zone Water Quality Model

Strategic management of nitrogen fertilizers can not only mitigate agricultural nitrogen pollution but also significantly enhance crop yield and nitrogen use efficiency. This study was designed to determine the optimal nitrogen fertilizer management strategy for the Yellow River irrigation area. Leveraging two years of field data related to soil water nitrogen and summer maize growth indices, parameters for the Root Zone Water Quality Model 2 (RZWQM2) were calibrated and validated. Subsequently, various scenarios were generated to simulate the impacts of different nitrogen application rates and basal chasing ratios on summer maize yield, nitrogen agronomic efficiency, nitrogen physiological efficiency, and nitrogen apparent recovery rate. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was employed for a comprehensive evaluation. RZWQM2 can effectively simulate the dynamic changes in soil moisture and nitrogen in the Yellow River irrigation area, and the results indicated that the mean relative error (MRE) between the simulated and observed values varied from 5.77% to 14.09%, and 4.36% to 33.01%, while the root mean square error (RMSE) ranged from 0.016 to 0.037 cm3/cm3, and 0.111 to 1.995 mg/kg. The normalized root mean square error (NRMSE) varied between 6.20% to 14.42% and 5.24% to 17.84%, respectively. The results validate the model’s effectiveness in simulating summer maize yields and nitrogen metrics under varying nitrogen fertilizer management practices. A nitrogen application rate of 180–200 kg/hm2 (expressed in terms of pure nitrogen) in the Yellow River irrigation area could adequately meet the requirements for summer maize production. The recommended nitrogen fertilizer management strategy in the Yellow River irrigation area involves applying 200 kg/hm2 of nitrogen in a 1:2:1 ratio during the sowing, trumpeting, and anthesis stages.

N-Map: High-resolution groundwater N-retention mapping and modelling by integration of geophysical, geological, geochemical, and hydrological data

A key aspect of protecting aquatic ecosystems from agricultural nitrogen (N) is to locate (i) farmlands where nitrate leaches from the bottom of the root zone and (ii) denitrifying zones in the aquifers where nitrate is removed before entering the surface water (N-retention). N-retention affects the choice of field mitigation measures to reduce delivered N to surface water. Farmland parcels associated with high N-retention gives the lowest impact of the targeted field measures and vice versa. In Denmark, a targeted N-regulation approach is currently implemented on small catchment scale (approx. 15 km2). Although this regulatory scale is much more detailed than what has been used previously, it is still so large that regulation for most individual fields will be either over- or under-regulated due to large spatial variation in the N-retention. The potential cost reduction for farmers is of up to 20–30% from detailed retention mapping at the field scale compared to the current small catchment scale.In this study, we present a mapping framework (N-Map) for differentiating farmland according to their N-retention, which can be used for improving the effectiveness of targeted N-regulation. The framework currently only includes N-retention in the groundwater. The framework benefits from the incorporation of innovative geophysics in hydrogeological and geochemical mapping and modelling. To capture and describe relevant uncertainties a large number of equally probable realizations are created through Multiple Point Statistical (MPS) methods. This allows relevant descriptions of uncertainties of parts of the model structure and includes other relevant uncertainty measures that affects the obtained N-retention. The output is data-driven high-resolution groundwater N-retention maps, to be used by the individual farmers to manage their cropping systems due to the given regulatory boundary conditions.The detailed mapping allows farmers to use this information in the farm planning in order to optimize the use of field measures to reduce delivered agricultural N to the surface water and thereby lower the costs of the field measures. From farmer interviews, however, it is clear that not all farms will have an economic gain from the detailed mapping as the mapping costs will exceed the potential economic gains for the farmers. The costs of N-Map is here estimated to 5–7 €/ha/year plus implementation costs at the farm. At the society level, the N-retention maps allow authorities to point out opportunities for a more targeted implementation of field measures to efficiently reduce the delivered N-load to surface waters.

Understanding barriers to adoption of sustainable nitrogen management practices in California

Achieving sustainability in agricultural nitrogen (N) management relies on farmers’ decisions to reduce fertilizer inputs and adopt conservation management practices. Understanding the drivers and barriers to farmers’ adoption of improved N management practices is critical to developing effective management and policy approaches on this intractable challenge. Existing research on farmer behavior has assumed that any barrier to adoption will result in lower practice adoption rates, without fully understanding how barriers may vary across different management practices, farm and farmer types, and stages of adoption. By leveraging two farmer survey data sets (total <i>n</i> &gt; 1,900), this study diagnoses key barriers to adoption across 11 different N management practices and a large diversity of farmer and farm types across the California Central Valley. We find resource constraints, technical knowledge, and uncertainty emerge as key barrier types that differentially affect farmers at various stages of adoption. On a practice-by-practice basis, uncertainty barriers appear greatest for nonadopters of a practice, whereas practice adopters are more likely to report resource barriers. Across management practices at the farm level, farmers with higher self-reported conservation orientations are more likely to report being affected by all barrier types, as compared to their peers with lower self-reported conservation orientations. Our findings demonstrate that barriers to adoption are more complex than simply the factors that predict lower adoption, as both adopters and nonadopters experience barriers. Furthermore, factors that typically predict higher adoption, such as conservation motivation, do not insulate a farmer from facing barriers to adoption. We consider how adopters are likely to go through a learning process while moving from considering to fully implementing a new practice, during which different barriers to behavior change may be encountered. We argue that interventions intended to motivate farmer adoption of improved management practices need to take more nuanced approaches to understanding how barriers to adoption are likely to vary across stages of adoption, farm and farmer type, and specific management practices.

Nitrogen inputs by irrigation is a missing link in the agricultural nitrogen cycle and related policies in Europe

Irrigation, one of the 28 agri-environmental indicators defined in the European Common Agricultural Policy, is often neglected in agricultural nitrogen (N) budgets, while it can be a considerable source of N in irrigated agriculture. The annual N input from irrigation water sources (NIrrig) to cropping systems was quantified for Europe for 2000–2010 at a resolution of 10 × 10 km, accounting for crop-specific gross irrigation requirements (GIR) and surface- and groundwater nitrate concentration. GIR were computed for 20 crops, while spatially explicit nitrate concentration in groundwater was derived using a random forest model. We show that although GIR were relatively stable (46–60 km3 yr-1), the Nirrig in Europe increased over the 10-year period (184 to 259 Gg N yr-1), approximately 68 % of which occurred in the Mediterranean region. The main hotspots appeared in areas with both high irrigation requirements and high groundwater nitrate concentration, reaching up to averaged values of 150 kg N ha-1 yr1. These were mainly located in Mediterranean Europe (Greece, Portugal and Spain) and to a lesser extent in Northern Europe (The Netherlands, Sweden and Germany). By not including NIrrig, environmental and agricultural policies are underestimating the real extent of N pollution hotspots in European irrigated systems.

Simulating nitrogen balance in Canadian agricultural soils from 1981 to 2016

Agriculture produces food, fiber and biofuels for the world's growing population, however, agriculture can be a major contributor of nitrogen (N) losses including emissions of ammonia (NH3), nitrous oxide (N2O) and nitrate (NO3−) leaching and runoff. A Canadian Agricultural Nitrogen Budget for Reactive N (CANBNr) model was developed to estimate the soil N balance in 3487 soil landscape of Canada polygons from 1981 to 2016. The CANBNr model integrates NH3 emission from fertilizers, manure from housing, storage and field, as well as direct/indirect N2O emissions from fertilizers, manures, crop residues and soil organic matter. The NO3− leaching is estimated based on the residual soil N (RSN) at harvest and drainage derived with the DeNitrification-DeComposition (DNDC) model. From 1981 to 2016, the N input from fertilizer and N fixation increased at a greater rate than N removal in harvested crops in all provinces of Canada, resulting in an increase in the RSN and N losses. In 2016, the Prairie provinces had lower N losses (11.7 kg N ha−1) from N2O, NH3 and NO3− compared with 43.2 kg N ha−1 in central Canada, and 76.5 kg N ha−1 in Atlantic Canada. However, the Prairie provinces had 84.3% of the total Canadian farmland (74.3% of the total Canadian N input), while central Canada had 12.9% of Canadian farmland (21.7% of the total Canadian N input). In the Prairie provinces, the total N2O loss from fertilizer N ranged 4.4–8.6 Gg N whereas NH3 loss ranged from 17.1 to 44.6 Gg N and these values were influenced by both emission intensity and total land area. Total N2O losses from manure were highest in Alberta, Ontario and Quebec resulting in 4.8, 4.4, and 3.4 Gg N and NH3 losses from manure were also highest in these 3 provinces at 61.1, 45.2 and 40.4 Gg N, respectively. Nitrate leaching was impacted by drainage volumes, soil type and N inputs. In the non-growing season, NO3− leaching losses (36-yr average) were 63.3 Gg in Ontario and 57.5 Gg N in Quebec compared with 20.8 Gg N for Ontario and 35.5 Gg N for Quebec in the growing season. In contrast, the Prairie provinces showed higher NO3− leaching in the growing season (23.1–37.4 Gg N) than in the non-growing season (10.4–13.7 Gg N). In summary, total fertilizer N increased the most over the 36 years in the Prairies which resulted in increased RSN and N leaching losses that will require further intervention.

Long-term changes of nitrogen leaching and the contributions of terrestrial nutrient sources to lake eutrophication dynamics on the Yangtze Plain of China

Abstract. Over the past half-century, drastically increased chemical fertilizers have entered agricultural ecosystems to promote crop production on the Yangtze Plain, potentially enhancing agricultural nutrient sources for eutrophication in freshwater ecosystems. However, long-term trends of nitrogen dynamics in terrestrial ecosystems and their impacts on eutrophication changes in this region remain poorly studied. Using a process-based ecosystem model, we investigated the temporal and spatial patterns of nitrogen use efficiency (NUE) and nitrogen leaching on the Yangtze Plain from 1979–2018. The agricultural NUE for the Yangtze Plain significantly decreased from 50 % in 1979 to 25 % in 2018, with the largest decline of NUE in soybean, rice, and rapeseed. Simultaneously, the leached nitrogen from cropland and natural land increased, with annual rates of 4.5 and 0.22 kg N ha−1 yr−2, respectively, leading to an overall increase of nitrogen inputs to the 50 large lakes. We further examined the correlations between terrestrial nutrient sources (i.e., the leached nitrogen, total phosphorus sources, and industrial wastewater discharge) and the satellite-observed probability of eutrophication occurrence (PEO) at an annual scale and showed that PEO was positively correlated with the changes in terrestrial nutrient sources for most lakes. Agricultural nitrogen and phosphorus sources were found to explain the PEO trends in lakes in the western and central part of the Yangtze Plain, and industrial wastewater discharge was associated with the PEO trends in eastern lakes. Our results revealed the importance of terrestrial nutrient sources for long-term changes in eutrophic status over the 50 lakes of the Yangtze Plain. This calls for region-specific sustainable nutrient management (i.e., nitrogen and phosphorus applications in agriculture and industry) to improve the water quality of lake ecosystems.

Modeling global oceanic nitrogen deposition from food systems and its mitigation potential by reducing overuse of fertilizers

Growing population and consumption pose unprecedented demands on food production. However, ammonia emissions mainly from food systems increase oceanic nitrogen deposition contributing to eutrophication. Here, we developed a long-term oceanic nitrogen deposition dataset (1970 to 2018) with updated ammonia emissions from food systems, evaluated the impact of ammonia emissions on oceanic nitrogen deposition patterns, and discussed the potential impact of nitrogen fertilizer overuse. Based on the chemical transport modeling approach, oceanic ammonia-related nitrogen deposition increased by 89% globally between 1970 and 2018, and now, it exceeds oxidized nitrogen deposition by over 20% in coastal regions including China Sea, India Coastal, and Northeastern Atlantic Shelves. Approximately 38% of agricultural nitrogen fertilizer was excessive, which corresponds to 15% of global oceanic ammonia-related nitrogen deposition. Policymakers and water quality managers need to pay increasingly more attention to ammonia associated with food production if the goal of reducing coastal nitrogen pollution is to be achieved for Sustainable Development Goals.

Climate change unequally affects nitrogen use and losses in global croplands.

Maintaining food production while reducing agricultural nitrogen pollution is a grand challenge under global climate change. Yet, the response of global agricultural nitrogen uses and losses to climate change on the temporal and spatial scales has not been fully characterized. Here, using historical data for 1961-2018 from over 150 countries, we show that global warming leads to small temporal but substantial spatial impacts on cropland nitrogen use and losses. Yield and nitrogen use efficiency increase in 29% and 56% of countries, respectively, whereas they reduce in the remaining countries compared with the situation without global warming in 2018. Precipitation and farm size changes would further intensify the spatial variations of nitrogen use and losses globally, but managing farm size could increase the global cropland nitrogen use efficiency to over 70% by 2100. Our results reveal the importance of reducing global inequalities of agricultural nitrogen use and losses to sustain global agriculture production and reduce agricultural pollution.

How much can changes in the agro-food system reduce agricultural nitrogen losses to the environment? Example of a temperate-Mediterranean gradient

Ammonia (NH3) volatilization, nitrous oxide (N2O) emissions, and nitrate (NO3−) leaching from agriculture cause severe environmental hazards. Research studies and mitigation strategies have mostly focused on one of these nitrogen (N) losses at a time, often without an integrated view of the agro-food system. Yet, at the regional scale, N2O, NH3, and NO3− loss patterns reflect the structure of the whole agro-food system. Here, we analyzed at the resolution of NUTS2 administrative European Union (EU) regions, N fluxes through the agro-food systems of a Temperate-Mediterranean gradient (France, Spain, and Portugal) experiencing contrasting climate and soil conditions. We assessed the atmospheric and hydrological N emissions from soils and livestock systems. Expressed per ha agricultural land, NH3 volatilization varied in the range 6.2–44.4 kg N ha−1 yr−1, N2O emission and NO3 leaching 0.3–4.9 kg N ha−1 yr−1 and 5.4–154 kg N ha−1 yr−1 respectively. Overall, lowest N2O emission was found in the Mediterranean regions, where NO3− leaching was greater. NH3 volatilization in both temperate and Mediterranean regions roughly follows the distribution of livestock density. We showed that these losses are also closely correlated with the level of fertilization intensity and agriculture system specialization into either stockless crop farming or intensive livestock farming in each region. Moreover, we explored two possible future scenarios at the 2050 horizon: (1) a scenario based on the prescriptions of the EU-Farm-to-Fork (F2F) strategy, with 25% of organic farming, 10% of land set aside for biodiversity, 20% reduction in N fertilizers, and no diet change; and (2) a hypothetical agro-ecological (AE) scenario with generalized organic farming, reconnection of crop and livestock farming, and a healthier human diet with an increase in the share of vegetal protein to 65% (i.e., the Mediterranean diet). Results showed that the AE scenario, owing to its profound reconfiguration of the entire agro-food system would have the potential for much greater reductions in NH3, N2O, and NO3− emissions, namely, 60–81% reduction, while the F2F scenario would only reach 24–35% reduction of N losses.

Is irrigation water an overlooked source of nitrogen in agriculture?

Is irrigation water an overlooked source of nitrogen in agriculture?