Review and analysis of global agricultural N₂O emissions relevant to the UK

Exploring dissolved N2O characteristics and unearthing indirect N2O emission factors in the shallow groundwater of paddy and upland fields

Indirect emissions of nitrous oxide (N2O) stemming from nitrogen (N) leaching in agricultural fields constitute a significant contributor to atmospheric N2O. Groundwater nitrate (NO3--N) pollution is severe in the Ningxia Yellow River Irrigation Area (NYRIA), coupled with high NO3--N leaching, exacerbates the risk of indirect N2O emissions from groundwater. Over two years of field observations, this study investigated the characteristics and interannual variations of dissolved N2O (dN2O) concentrations and indirect N2O emission factors (EF5g) in shallow groundwater. The research focused on three typical farmlands in the NYRIA, each subjected to six levels of N fertilizer application. The mean dN2O concentrations in the groundwater of paddy, corn and vegetable fields were 5.17, 8.40 and 16.35 μg N·L-1, respectively. Notably, the dN2O concentrations in the shallow groundwater of upland fields exceeded those in paddy fields, with maximum levels in vegetable fields nearly an order of magnitude higher. Elevated N application significantly increased dN2O concentrations across various farmlands, showing statistically significant variation. However, differences in EF5g-A and EF5g-B within the same farmland were negligible. Denitrification was the primary process contributing to N2O production in groundwater, with nitrification also played a crucial role in upland fields. Factors such as NO3--N, NH4+-N, dissolved oxygen (DO), and pH critically influenced N2O production. EF5g-B, which considers the NO3--N consumption during denitrification processes in groundwater, was deemed more appropriate than EF5g-A for assessing the indirect N2O emission in the NYRIA. The EF5g of agricultural fields exhibited minimal sensitivity to N input but was significantly affected by other factors, such as the planting pattern. The study revealed the rationality of adopting EF5g-B in assessing indirect N2O emissions, providing valuable insights for N management strategies in regions with high NO3--N leaching. Minimizing N fertilizer application while ensuring crop yield, especially in upland fields, is beneficial for reducing N2O emissions.

Estimating soil N2O emissions induced by organic and inorganic fertilizer inputs using a Tier-2, regression-based meta-analytic approach for U.S. agricultural lands

Consistent methods are essential for generating country and region-specific estimates of greenhouse gas (GHG) emissions used for reporting and policymaking. The estimates of direct N2O emissions from U.S. agricultural soils have primarily relied on the use of emission factors (EFs, Tier-1) and process-based models (Tier-3). However, Tier-1 estimates are relatively crude while Tier-3 calculations can be costly. This work addressed this gap by developing a Tier-2, regression-based approach by leveraging a meta-database containing 1883 field N2O observations together with environmental and management covariates from 139 studies. Our results estimated higher monthly soil N2O emissions (N2Om, kg N/ha) during the growing season (0.38) than the fallow period (0.15), highlighting the importance of considering measurement periods when utilizing meta-databases for analyzing N2O drivers. Significantly different N2Om were found for tillage practices (conventional > no-till: 0.42 > 0.27), fertilizer type (liquid > solid manure: 0.55 > 0.32), and soil texture (fine > coarse: 0.36 > 0.22). The comparisons of the influence of crop type and rotation, water management, and soil order on N2O emissions are complicated by regional data availability and interactions among different factors. Additionally, the finding that N2O emissions reported based on area (N2Om), N input rate (EF), or yield can alter treatment rankings underscores the need to establish transparent criteria for rewarding or discouraging regionally-based management practices using N2O metrics. Finally, we show how General Linear Models (GLMs) can be used to estimate country and regional Tier-2 N2Om using a suite of covariates. Our GLMs identified tillage, water management, N input type and rate, soil properties, and elevation as the most influential covariates for the conterminous U.S. The limited accuracy of regional-scale GLMs, however, suggests the need to further improve the quality and availability of GHG and covariate data through concerted efforts in data collection.

Global N2O emissions from our planet: Which fluxes are affected by man, and can we reduce these?

In some places, N2O emissions have doubled during the last 2-3 decades. Therefore, it is crucial to identify N2O emission hotspots from terrestrial and aquatic systems. Large variation in N2O emissions occur in managed as well as in natural areas. Natural unmanaged tropical and subtropical wet forests are important N2O sources globally. Emission hotspots, often coupled to human activities, vary across climate zones, whereas N2O emissions are most often a few kg N ha-1 year-1 from arable soils, drained organic soils in the boreal and temperate zones often release 20-30 kg N ha-1 year-1. Similar high N2O emissions occur from some tropical crops like tea, palm oil and bamboo. This strong link between increased N2O emissions and human activities highlight the potential to mitigate large emissions. In contrast, water where oxic and anoxic conditions meet are N2O emission hotspots as well, but not possible to reduce.

Influence of key factors on ammonia and nitrous oxide emission factors for excreta deposited by livestock and land-applied manure

Ammonia (NH3) and nitrous oxide (N2O) emissions from livestock manure management have a significant impact on air quality and climate change. There is an increasing urgency to improve our understanding of drivers influencing these emissions. We analysed the DATAMAN ("DATAbase for MANaging greenhouse gas and ammonia emissions factors") database to identify key factors influencing (i) NH3 emission factors (EFs) for cattle and swine manure applied to land and (ii) N2O EFs for cattle and swine manure applied to land, and (iii) cattle urine, dung and sheep urine deposited during grazing. Slurry dry matter (DM) content, total ammoniacal nitrogen (TAN) concentration and method of application were significant drivers of NH3 EFs from cattle and swine slurry. Mixed effect models explained 14-59 % of the variance in NH3 EFs. Apart from the method of application, the significant influence of manure DM, manure TAN concentration or pH on NH3 EFs suggests mitigation strategies should focus on these. Identifying key factors influencing N2O EFs from manures and livestock grazing was more challenging, likely because of the complexities associated with microbial processes and soil physical properties impacting N2O production and emissions. Generally, significant factors were soil-related e.g. soil water content, pH, clay content, suggesting mitigations may need to consider the conditions of the receiving environment for manure spreading and grazing deposition. Total variability explained by terms in mixed effect model was on average 66 %, with the random effect 'experiment identification number' explaining, on average, 41 % of the total variability in the models. We suspect this term captured the effect of non-measured manure, soil and climate factors and any biases in application and measurement technique effects associated with individual experiments. This analysis has helped to improve our understanding of key factors of NH3 and N2O EFs for inclusion within models. With more studies over time, insights into the underlying processes influencing emissions will be further improved.

Long-term variability in N2O emissions and emission factors for corn and soybeans induced by weather and management at a cold climate site

Nitrous oxide (N2O) emissions are highly variable in space and time due to the complex interplay between soil, management practices and weather conditions. Micrometeorological techniques integrate emissions over large areas at high temporal resolution. This allows identification of causes of intra- and inter-annual variability of N2O emissions and development of robust emission factors (EF). Here, we investigated factors responsible for variability in N2O emissions during growing and non-growing seasons of corn and soybeans grown in an imperfectly drained silt loam soil, in Ontario, Canada. We used quasi-continuously (at half-hourly to hourly intervals) N2O fluxes measured via the flux-gradient technique over 11 years for corn and 5 years for soybeans and evaluated the uncertainty of default IPCC and Canada-specific EFs. In the growing season, emissions were controlled by soil nitrate content, soil moisture and temperature in the fertilized corn, while moisture and temperature regulated N2O emissions in the unfertilized soybeans. In the non-growing season, nitrogen (N) input from the crop residue did not affect the emissions, pointing to freeze-thaw cycles as mechanisms for enhanced N2O emissions. The non-growing season contribution to annual emissions was 38% in corn and 43% in soybeans. On average, annual emissions were 2.6-fold higher in corn than soybeans. Observed mean N2O EFs were 0.84% (0.12-2.02%) for growing season and 1.69% (0.29-7.32%) for yearly emissions. The growing season EF derived from long-term N2O emissions was 0.9 ± 0.14%. The interannual variability in N2O emissions and EFs can be attributed to management practices and annual weather variability. The default IPCC approach based on overall N input had poorer performance in predicting annual N2O emissions compared to the current Canadian methodology, which includes management and environmental factor in addition to N inputs. The observed emissions were further evaluated with a newly developed growing season N2O emission prediction approach for Canada. However, performance of the approach was poorer than IPCC or the current national Canadian approach. Additional tests of the new national methodology are recommended as well as consideration of non-growing season emissions.

Quantifying the effects of anaerobic soil disinfestation and other biological soil management strategies on nitrous oxide emissions from raised bed plasticulture tomato production

Soilborne pests are a major obstacle that must be overcome for the production of horticultural crops. Methyl bromide (MBr) was an effective preplanting soil broad-spectrum biocide, but its use has been banned due to its role in depleting the ozone layer. As a result, sustainable alternative methods for controlling soilborne pathogens and pests are needed. Nitrous oxide (N₂ O) emissions are of concern in crop production due to the role of N₂ O as a greenhouse gas. Agricultural lands are known sources for emission of N₂ O into the atmosphere. Emissions are related to many environmental factors as well as fertilization and fumigation practices. This study evaluated the influence of different alternatives to MBr on N₂ O emissions throughout a tomato production season in two locations representative of southern and northern Florida. We evaluated eight soil management practices, including (a) untreated controls; (b) chemical soil fumigation; (c) anaerobic soil disinfestation using molasses (M) + composted poultry litter and (d and e) M + composted yard waste (CYW, at two rates); (f) Soil Symphony Amendment (SSA), a commercially available mix of microbes and nutrients; (g) CYW alone; and (h) CYW + SSA. Nitrous oxide emissions were measured throughout the cropping season. Emissions were highest on the day of planting (Day 21), ranging from 213 to 1,878 μg m^-2 h^-1 , likely due to the release of N₂ O that had accumulated under the totally impermeable film when it was punctured for planting. However, statistical significance varied between sites. Estimated cumulative emissions of N₂ O throughout the production season ranged from 1.3 to 4.8 kg N₂ O-N ha^-1 .

Uncertainties in direct N2O emissions from grazing ruminant excreta (EF3PRP) in national greenhouse gas inventories

Excreta deposition onto pasture, range and paddocks (PRP) by grazing ruminant constitute a source of nitrous oxide (N₂O), a potent greenhouse gas (GHG). These emissions must be reported in national GHG inventories, and their estimation is based on the application of an emission factor, EF_3PRP (proportion of nitrogen (N) deposited to the soil through ruminant excreta, which is emitted as N₂O)_. Depending on local data available, countries use various EF_3PRPs and approaches to estimate N₂O emissions from grazing ruminant excreta. Based on ten case study countries, this review aims to highlight the uncertainties around the methods used to account for these emissions in their national GHG inventories, and to discuss the efforts undertaken for considering factors of variation in the calculation of emissions. Without any local experimental data, 2006 the IPCC default (Tier 1) EF_3PRPs are still widely applied although the default values were revised in 2019. Some countries have developed country-specific (Tier 2) EF_3PRP based on local field studies. The accuracy of estimation can be improved through the disaggregation of EF_3PRP or the application of models; two approaches including factors of variation. While a disaggregation of EF_3PRP by excreta type is already well adopted, a disaggregation by other factors such as season of excreta deposition is more difficult to implement. Empirical models are a potential method of considering factors of variation in the establishment of EF_3PRP. Disaggregation and modelling requires availability of sufficient experimental and activity data, hence why only few countries have currently adopted such approaches. Replication of field studies under various conditions, combined with meta-analysis of experimental data, can help in the exploration of influencing factors, as long as appropriate metadata is recorded. Overall, despite standard IPCC methodologies for calculating GHG emissions, large uncertainties and differences between individual countries' accounting remain to be addressed.

A global meta-analysis of nitrous oxide emission from drip-irrigated cropping system

Drip irrigation is a useful practice to enhance water and fertilizer nitrogen (N) use efficiency. However, the use of drip irrigation to mitigate nitrous oxide (N₂ O) emissions in agricultural systems globally is uncertain. Here, we performed a global meta-analysis of 485 field measurements of N₂ O emissions from 74 peer-reviewed publications prior to March 2021, to quantify the fertilizer-induced N₂ O emission factor (EF) of drip irrigation and examine the influencing factors of climate, crop, soil properties, and source and rate of fertilizer N application. The results showed that drip irrigation reduced (p < 0.05) N₂ O emissions by 32% and 46% compared to furrow and sprinkler irrigation systems, respectively. The overall average EF with drip irrigation was 0.35%, being two-thirds lower than the IPCC Tier I default value of 1% (kg N₂ O-N/kg added fertilizer N). The EF was not significantly affected by climate, crop, soil texture, soil organic carbon content, and pH. The EF was also not significantly (p > 0.05) affected by synthetic N fertilizer source despite a lower numerical value with enhanced efficiency than conventional fertilizers. The EF increased significantly (p < 0.001) with N addition rate in a binomial distribution. Using the IPCC default EF overestimated N₂ O emissions inventories for drip-irrigated cropping systems by 7614 and 13,091 Mg per year for China and the globe, respectively. These results indicate that drip irrigation should be recommended as an essential N₂ O mitigation strategy for irrigated crop production.

Effects of biochar on nitrification and denitrification-mediated N2O emissions and the associated microbial community in an agricultural soil

Nitrous oxide (N₂O) is a strong greenhouse gas, and it is of great significance for N₂O reduction to study the effects of biochar on its production pathway. In this research, the contributions and mechanisms of biochar on autotrophic nitrification (ANF), heterotrophic nitrification (HNF), and denitrification (DF) to N₂O emissions were studied by using ¹⁵N stable isotopes and high-throughput sequencing after laboratory incubation. The results showed that biochar addition at 2% (B2) significantly reduced the N₂O emissions from the ANF by an average of 20.6%, while adding 5% biochar (B5) had no significant effect on the ANF. Both B2 and B5 significantly reduced the N₂O emissions from the HNF by 15.7% and 13.2%, respectively, and reduced the N₂O emissions from the DF by 40.9% and 11.7%, respectively. B2 enhanced the relative contribution rate of the ANF to N₂O emissions by 6.3%, while B5 had little effect on it. Biochar addition significantly changed the copy numbers of the AOA and AOB, as well as the nirK, nirS, and nosZ genes, but it had no significant effect on the community composition of the AOA and had minimal effect on the AOB community. B2 significantly increased the abundance of the genus Rhodococcus of nirK type denitrifiers and had a significant effect on the relative abundance of Cupriavidus and Pseudomonas of the nosZ type denitrifiers. These results revealed that the inhibitory effects of biochar on N₂O emissions from nitrification might be attributed to the direct immobilization and adsorption of inorganic N by biochar and to its promotion of the genus Rhodococcus of nirK-type denitrifiers and the genera Cupriavidus and Pseudomonas of the nosZ-type denitrifiers. The soil exchangeable NH₄⁺-N and NO₃^--N concentrations were the primary factors affecting the N₂O emission rates. These results help to elucidate the effects and mechanisms of biochar on N₂O production pathways in agricultural soil.

Elucidating three-way interactions between soil, pasture and animals that regulate nitrous oxide emissions from temperate grazing systems

Pasture-based livestock farming contributes considerably to global emissions of nitrous oxide (N2O), a powerful greenhouse gas approximately 265 times more potent than carbon dioxide. Traditionally, the estimation of N2O emissions from grasslands is carried out by means of plot-scale experiments, where externally sourced animal excreta are applied to soils to simulate grazing conditions. This approach, however, fails to account for the impact of different sward types on the composition of excreta and thus the functionality of soil microbiomes, creating unrealistic situations that are seldom observed under commercial agriculture. Using three farming systems under contrasting pasture management strategies at the North Wyke Farm Platform, an instrumented ruminant grazing trial in Devon, UK, this study measured N2O emissions from soils treated with cattle urine and dung collected within each system as well as standard synthetic urine shared across all systems, and compared these values against those from two forms of controls with and without inorganic nitrogen fertiliser applications. Soil microbial activity was regularly monitored through gene abundance to evaluate interactions between sward types, soil amendments, soil microbiomes and, ultimately, N2O production. Across all systems, N2O emissions attributable to cattle urine and standard synthetic urine were found to be inconsistent with one another due to discrepancy in nitrogen content. Despite previous findings that grasses with elevated levels of water-soluble carbohydrates tend to generate lower levels of N2O, the soil under high sugar grass monoculture in this study recorded higher emissions when receiving excreta from cattle fed the same grass. Combined together, our results demonstrate the importance of evaluating environmental impacts of agriculture at a system scale, so that the feedback mechanisms linking soil, pasture, animals and microbiomes are appropriately considered.

Global Research Alliance N2 O chamber methodology guidelines: Statistical considerations, emission factor calculation, and data reporting

Static chambers are often used for measuring nitrous oxide (N₂ O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N₂ O fluxes. Because N₂ O chamber measurements are commonly used to assess N₂ O mitigation strategies or to determine country-specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N₂ O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non-normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N₂ O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N₂ O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Meta-analysis of New Zealand's nitrous oxide emission factors for ruminant excreta supports disaggregation based on excreta form, livestock type and slope class

Globally, animal excreta (dung and urine) deposition onto grazed pastures represents more than half of anthropogenic nitrous oxide (N₂O) emissions. To account for these emissions, New Zealand currently employs urine and dung emission factor (EF₃) values of 1.0% and 0.25%, respectively, for all livestock. These values are primarily based on field studies conducted on fertile, flatland pastures predominantly used for dairy cattle production but do not consider emissions from hill land pastures primarily used for sheep, deer and non-dairy cattle. The objective of this study was to determine the most suitable urine and dung EF₃ values for dairy cattle, non-dairy cattle, and sheep grazing pastures on different slopes based on a meta-analysis of New Zealand EF₃ studies. As none of the studies included deer excreta, deer EF₃ values were estimated from cattle and sheep values. The analysis revealed that a single dung EF₃ value should be maintained, although the value should be reduced from 0.25% to 0.12%. Furthermore, urine EF₃ should be disaggregated by livestock type (cattle > sheep) and topography (flatland and low sloping hill country > medium and steep sloping hill country), with EF₃ values ranging from 0.08% (sheep urine on medium and steep slopes) to 0.98% (dairy cattle on flatland and low slopes). While the mechanism(s) causing differences in urine EF₃ values for sheep and cattle are unknown, the 'slope effect' on urine EF₃ is partly due to differences in soil chemical and physical characteristics, which influence soil microbial processes on the different slope classes. The revised EF₃ values were used in an updated New Zealand inventory approach, resulting in 30% lower national N₂O emissions for 2017 compared to using the current EF₃ values. We recommend using the revised EF₃ values in New Zealand's national greenhouse gas inventory to more accurately capture N₂O emissions from livestock grazing.

Meta-analysis of global livestock urine-derived nitrous oxide emissions from agricultural soils

Nitrous oxide (N2 O) is an air pollutant of major environmental concern, with agriculture representing 60% of anthropogenic global N2 O emissions. Much of the N2 O emissions from livestock production systems result from transformation of N deposited to soil within animal excreta. There exists a substantial body of literature on urine patch N2 O dynamics, we aimed to identify key controlling factors influencing N2 O emissions and to aid understanding of knowledge gaps to improve GHG reporting and prioritize future research. We conducted an extensive literature review and random effect meta-analysis (using REML) of results to identify key relationships between multiple potential independent factors and global N2 O emissions factors (EFs) from urine patches. Mean air temperature, soil pH and ruminant animal species (sheep or cow) were significant factors influencing the EFs reviewed. However, several factors that are known to influence N2 O emissions, such as animal diet and urine composition, could not be considered due to the lack of reported data. The review highlighted a widespread tendency for inadequate metadata and uncertainty reporting in the published studies, as well as the limited geographical extent of investigations, which are more often conducted in temperate regions thus far. Therefore, here we give recommendations for factors that are likely to affect the EFs and should be included in all future studies, these include the following: soil pH and texture; experimental set-up; direct measurement of soil moisture and temperature during the study period; amount and composition of urine applied; animal type and diet; N2 O emissions with a measure of uncertainty; data from a control with zero-N application and meteorological data.

Multi-objective optimization as a tool to identify possibilities for future agricultural landscapes

Agricultural landscapes provide many functions simultaneously including food production, regulation of water and regulation of greenhouse gases. Thus, it is challenging to make land management decisions, particularly transformative changes, that improve on one function without unintended consequences for other functions. To make informed decisions the trade-offs between different landscape functions must be considered. Here, we use a multi-objective optimization algorithm with a model of crop production that also simulates environmental effects such as nitrous oxide emissions to identify trade-off frontiers and associated possibilities for agricultural management. Trade-offs are identified in three soil types, using wheat production in the UK as an example, then the trade-off for combined management of the three soils is considered. The optimization algorithm identifies trade-offs between different objectives and allows them to be visualised. For example, we observed a highly non-linear trade-off between wheat yield and nitrous oxide emissions, illustrating where small changes might have a large impact. We used a cluster analysis to identify distinct management strategies with similar management actions and use these clusters to link the trade-off curves to possibilities for management. There were more possible strategies for achieving desirable environmental outcomes and remaining profitable when the management of different soil types was considered together. Interestingly, it was on the soil capable of the highest potential profit that lower profit strategies were identified as useful for combined management. Meanwhile, to maintain average profitability across the soils, it was necessary to maximise the profit from the soil with the lowest potential profit. These results are somewhat counterintuitive and so the range of strategies supplied by the model could be used to stimulate discussion amongst stakeholders. In particular, as some key objectives can be met in different ways, stakeholders could discuss the impact of these management strategies on other objectives not quantified by the model.

An efficient framework for conducting systematic literature reviews in agricultural sciences

Systematic review has generally been accepted as an effective, more complete, repeatable, and less biased type literature review that can successfully lead to evidence-based conclusions. This study attempts to develop a framework for systematic review with guidelines on how to conduct an effective systematic review for agricultural research. Systematic reviews require more time and effort but they can be used to conduct a comprehensive literature review, identifying potentially eligible articles on primary agricultural research and answering certain focused questions. A systematic review is also conducted as an example to examine whether systematic reviews are used in agricultural sciences. It was found that in the last two decades about a third (N = 29 out of 89 or 32.5%) of the eligible studies, classified as reviews related to agricultural research, are available as free full-text from publisher, while only eighteen of them were finally eligible to be included in this systematic review.

Dynamics and emissions of N2O in groundwater: A review

This work reviews the concentrations, the dynamics and the emissions of nitrous oxide (N₂O) in groundwater. N₂O is an important greenhouse gas (GHG) and the primary stratospheric ozone depleting substance. The major anthropogenic source that contributes to N₂O generation in aquifers is agriculture because the use of fertilizers has led to the widespread groundwater contamination by inorganic nitrogen (N) (mainly nitrate, NO₃^-). Once in the aquifer, this inorganic N is transported and affected by several geochemical processes that produce and consume N₂O. An inventory of dissolved N₂O concentrations is presented and the highest concentration is about 18.000 times higher than air-equilibrated water (up to 4004μg N L^-1). The accumulation of N₂O in groundwater is mainly due to denitrification and to lesser extent to nitrification. Their occurrence depend on the geochemical (e.g., NO₃^-, dissolved oxygen, ammonium and dissolved organic carbon) as well as hydrogeological parameters (e.g., groundwater table fluctuations and aquifer permeability). The coupled understanding of both parameters is necessary to gain insight on the dynamics and the emissions of N₂O in groundwater. Overall, groundwater indirect N₂O emissions seem to be a minor component of N₂O emissions to the atmosphere. Further research might be devoted to evaluate the groundwater contribution to the indirect emissions of N₂O because this will help to better constraint the N₂O global budget and, consequently, the N budget.

Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems

Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers.