It is essential to increase food production to meet the projected population increase while reducing environmental loads. Biological nitrification inhibition (BNI)-enabled wheat genetic stocks are under development through chromosome engineering by transferring chromosomal regions carrying the BNI trait from a wild relative (Leymus racemosus (Lam.) Tzvelev) into elite wheat varieties; field evaluation of these newly developed BNI-wheat varieties has started. Ten years from now, BNI-enabled elite wheat varieties are expected to be deployed in wheat production systems. This study aims to evaluate the impacts of introducing these novel genetic solutions on life cycle greenhouse gas (LC-GHG) emissions, nitrogen (N) fertilizer application rates and N-use efficiency (NUE). Scenarios were developed based on evidence of nitrification inhibition and nitrous oxide (N2O) emission reduction by BNI crops and by synthetic nitrification inhibitors (SNIs), as both BNI-wheat and SNIs slow the nitrification process. Scenarios including BNI-wheat will inhibit nitrification by 30% by 2030 and 40% by 2050. It was assumed that N fertilizer application rates can potentially be reduced, as N losses through N2O emissions, leaching and runoff are expected to be lower. The results show that the impacts from BNI-wheat with 40% nitrification inhibition by 2050 are assessed to be positive: a 15.0% reduction in N fertilization, a 15.9% reduction in LC-GHG emissions, and a 16.7% improvement in NUE at the farm level. An increase in ammonia volatilization had little influence on the reduction in LC-GHG emissions. The GHG emissions associated with N fertilizer production and soil N2O emissions can be reduced between 7.3 and 9.5% across the wheat-harvested area worldwide by BNI-wheat with 30% and 40% nitrification inhibition, respectively. However, the present study recommends further technological developments (e.g. further developments in BNI-wheat and the development of more powerful SNIs) to reduce environmental impacts while improving wheat production to meet the increasing worldwide demand.

Among alternative tillage practices, conservation tillage (CT) is a prominent greenhouse gas (GHG) mitigation strategy advocated in wheat cultivation, largely because of its low energy consumption and minimum soil disturbance during cultural operations. This paper examines the agricultural production and GHG emission trade-off of CT vis-à-vis traditional tillage (TT) on wheat farms of Bangladesh. Using a directional distance function approach, the maximum reduction in GHG emissions was searched for within all available tillage technology options, while increasing wheat production as much as possible. The underlying institutional, technical, and other socio-economic factors determining the efficient use of CT were analyzed using a fractional regression model. The average meta-efficiency score for permanent bed planting (PBP) and strip tillage (ST) was 0.89, while that achieved using power tiller operated seeders (PTOS) is 0.87. This indicates that with the given input sets, there is potential to reduce GHG emissions by about 11% for ST and PTOS; that potential is 13% for farmers using PTOS. The largest share of TT farmers cultivate wheat at lower meta-efficiency levels (0.65–0.70) compared to that observed with farmers practicing CT (0.75–0.80). Fractional regression model estimates indicate that an optimal, timely dose of fertilizers with a balanced dose of nutrients is required to reduce GHG emissions. To develop climate smart sustainable intensification strategies in wheat cultivation, it is important to educate farmers on efficient input management and CT together. Agricultural development programs should focus on addressing heterogeneities in nutrient management in addition to tillage options within CT.

no sp. Assessment of Nitrogen Fluxes to Air and Water from Site Scale to Continental Scale | The aim of this study is to illustrate the importance of farm scale heterogeneity on nitrogen (N) losses in agricultural landscapes. Results are exemplified with a chain of N models calculating farm-N balances and distributing the N-surplus to N-losses (volatilisation, denitrification, leaching) and soil-N accumulation/release in a Danish landscape. Possible non-linearities in upscaling are assessed by comparing average model results based on (i) individual farm level calculations and (ii) averaged inputs at landscape level. Effects of the non-linearities that appear when scaling up from farm to landscape are demonstrated. Especially in relation to ammonia losses the non-linearity between livestock density and N-loss is significant (p > 0.999), with around 20-30% difference compared to a scaling procedure not taking this non-linearity into account. A significant effect of farm type on soil N accumulation (p > 0.95) was also identified and needs to be included when modelling landscape level N-fluxes and greenhouse gas emissions.

no sp. Assessment of Nitrogen Fluxes to Air and Water from Site Scale to Continental Scale | The aim of this study is to illustrate the importance of farm scale heterogeneity on nitrogen (N) losses in agricultural landscapes. Results are exemplified with a chain of N models calculating farm-N balances and distributing the N-surplus to N-losses (volatilisation, denitrification, leaching) and soil-N accumulation/release in a Danish landscape. Possible non-linearities in upscaling are assessed by comparing average model results based on (i) individual farm level calculations and (ii) averaged inputs at landscape level. Effects of the non-linearities that appear when scaling up from farm to landscape are demonstrated. Especially in relation to ammonia losses the non-linearity between livestock density and N-loss is significant (p > 0.999), with around 20-30% difference compared to a scaling procedure not taking this non-linearity into account. A significant effect of farm type on soil N accumulation (p > 0.95) was also identified and needs to be included when modelling landscape level N-fluxes and greenhouse gas emissions.

This study evaluated the greenhouse gas emissions of solid dairy manure storage with the micro-aerobic group (MA; oxygen concentration <5%) and control group (CK; oxygen concentration <1%), and explained the difference in greenhouse gas emissions by exploring bacterial community succession. The results showed that the MA remained the micro-aerobic conditions, which the maximum and average oxygen concentrations were 4.1% and 1.9%, respectively; while the average oxygen concentrations of the CK without intervention management was 0.5%. Compared with the CK, carbon dioxide and methane emissions in MA were reduced by 78.68% and 99.97%, respectively, and nitrous oxide emission was increased by almost three times with a small absolute loss, but total greenhouse gas emissions decreased by 91.23%. BugBase analysis showed that the relative abundance of aerobic bacteria in CK decreased to 0.73% on day 30, while that in MA increased to 6.56%. Genus MBA03 was significantly different between the two groups (p < 0.05) and was significantly positively correlated with carbon dioxide and methane emissions (p < 0.05). A structural equation model also revealed that the oxygen concentration and MBA03 of the MA had significant direct effects on methane emission rate (p < 0.001). The research results could provide theoretical basis and measures for directional regulation of greenhouse gas emission reduction during dairy manure storage.

Potato (Solanum tuberosum L.) production in irrigated coarse-textured soils requires intensive nitrogen (N) fertilization which may increase reactive N losses. Biological soil additives including N-fixing microbes (NFM) have been promoted as a means to increase crop N use efficiency, though few field studies have evaluated their effects, and none have examined the combined use of NFM with microbial inhibitors. A 2-year study (2018–19) in an irrigated loamy sand quantified the effects of the urease inhibitor NBPT, the nitrification inhibitor DMPSA, NFM, and the additive combinations DMPSA + NBPT and DMPSA + NFM on potato performance and growing season nitrous oxide (N₂O) emissions and nitrate (NO₃⁻) leaching. All treatments, except a zero-N control, received diammonium phosphate at 45 kg N ha⁻¹ and split applied urea at 280 kg N ha⁻¹. Compared with urea alone, DMPSA + NBPT reduced NO₃⁻ leaching and N₂O emissions by 25% and 62%, respectively, and increased crop N uptake by 19% in one year, although none of the additive treatments increased tuber yields. The DMPSA and DMPSA + NBPT treatments had greater soil ammonium concentration, and all DMPSA-containing treatments consistently reduced N₂O emissions, compared to urea-only. Use of NBPT by itself reduced NO₃⁻ leaching by 21% across growing seasons and N₂O emissions by 37% in 2018 relative to urea-only. In contrast to the inhibitors, NFM by itself increased N₂O by 23% in 2019; however, co-applying DMPSA with NFM reduced N₂O emissions by ≥ 50% compared to urea alone. These results demonstrate that DMPSA can mitigate N₂O emissions in potato production systems and that DMPSA + NBPT can reduce both N₂O and NO₃⁻ losses and increase the N supply for crop uptake. This is the first study to show that combining a nitrification inhibitor with NFM can result in decreased N₂O emissions in contrast to unintended increases in N₂O emissions that can occur when NFM is applied by itself.

Increasing indirect nitrous oxide (N₂O) emission from river networks as a result of enhanced human activities on landscapes has become a global issue, as N₂O has been widely recognized as an important ozone-depleting greenhouse gas. However, indirect N₂O emissions from different rivers, particularly for those that drain completely different landscapes, are poorly understood. Here, we investigated the spatial-temporal variability of N₂O emissions among the different rivers in the Chaohu Lake Basin of Eastern China. Our results showed that river reaches in urban watersheds are the hotspots of N₂O production, with a mean N₂O concentration of ∼410 nmol L⁻¹, which is 9–18 times greater than those mainly draining forested (23 nmol L⁻¹), agricultural (42 nmol L⁻¹) and mixed (45 nmol L⁻¹) landscapes. Riverine dissolved N₂O was generally supersaturated with respect to the atmosphere. Such N₂O saturation can best be explained by nitrogen availability, except for those in the forested watersheds, where dissolved oxygen is thought to be the primary predictor. The estimated N₂O fluxes in urban rivers reached ∼471 μmol m⁻² d⁻¹, a value of ∼22, 13, and 11 times that in forested, agricultural and mixed watersheds, respectively. Averaged riverine N₂O emission factors (EF₅ᵣ) of the forested, agricultural, urban and mixed watersheds were 0.066%, 0.12%, 0.95% and 0.16%, respectively, showing different deviations from the default EF₅ᵣ that released by IPCC in 2019. This points to a need for more field measurements with wider spatial coverage and finer frequency to further refine the EF₅ᵣ and to better reveal the mechanisms behind indirect N₂O emissions as influenced by watershed landscapes.

Nitrogen (N) deposition in China may increase due to urbanization and economic growth. Current research has considered the ecological significance under the assumption of increasing N deposition. Atmospheric N deposition tending toward levelling or declining has been observed in China. Such potential recovery and responses of high N loads ecosystems under decreasing atmospheric N deposition scenarios have yet to be adequately investigated. This work reviews existing literature to consider possible responses of carbon (C) sequestration, biodiversity and species composition, soil acidification, and greenhouse emissions in ecosystems responding to recent patterns of N deposition. Potential effects of N composition and internal ratios may be further explored through state-of-the-art N addition experiments and model development.

Estuaries are considered hot spots for the production and emissions of nitrous oxide (N2O) and easily occur suspended particles (SPS), however, current understanding about the role of SPS in the N2O emissions from the oxic estuarine waters of lacustrine ecosystems is still limited. In this study, field investigations were performed in the estuaries of hypereutrophic Taihu Lake, and laboratory simulations were simultaneously conducted to ascertain the characteristics of N2O emissions with different SPS concentrations. The results showed that the N2O emission fluxes ranged from 9.75 to 118.38 μg m−2 h−1, indicating a high spatial heterogeneity for the N2O emissions from the estuaries of Taihu Lake. Although the dissolved oxygen (DO) concentrations were up to 7.85 mg L−1 in the estuarine waters, from where the N2O emissions fluxes were approximately three times that of the lake regions. Multiple regression model selected the total nitrogen (TN), SPS, and DO concentrations as the crucial factors influencing the N2O emission fluxes. Particularly for SPS, the simulation results showed that the N2O concentrations increased gradually with the increase in the SPS concentrations of an oxic water column containing 4 mg L−1 of NO3−-N, indicating that a high SPS concentration can accelerate the N2O emissions. It was related to the change of denitrifying bacteria population in the SPS, as evidenced by its significantly positive correlation with N2O emissions (p < 0.01). Our findings will draw attentions to the role of SPS playing in the N2O productions and emissions in eutrophic lakes, and its effect on nitrogen cycle should be considered in the future study.

Baseline emission values of greenhouse gases were not well established for commercial poultry barns in cold regions, including Canada, due to a lack of well-designed field studies. Emission factors of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O), were acquired for a commercial broiler barn and cage-layer barn in the Canadian Prairies climate. Between March 2015 and February 2016, monthly measurements throughout the year for the layer barn and over 6 flocks for the broiler barn, and diurnal measurements in the mild, warm, and cold seasons for both barns were conducted, respectively. The ventilation rate was estimated based on a CO₂ mass balance method; thus CO₂ emissions were quantified by the CIGR (2002) models. The CH₄ and N₂O emissions present at low levels from global perspective for both barns; the cold climate proved to be a major reason for the lower CH₄ emission from the layer barn. Considerable seasonal effect was observed only for N₂O emissions from the broiler barn, and for CH₄ and N₂O emissions from the layer barn, both with higher emissions in the mild and warm seasons than in the cold season. The big diurnal variations of CO₂ emissions for the layer barn demonstrated the uncertainty of the seasonal results by snapshot measurements and correction factors (from −20.9% to −22.5%) were obtained. Besides, the difference of CH₄ and N₂O concentrations and emissions as well as CO₂ concentrations between best-case (the first day after manure removal) and worst-case conditions (the last day before manure removal) was not obvious for the layer barn. Additionally, changes of temperature and ventilation rate were likely to have more impact on N₂O emission for the broiler barn and more impact on CH₄ emission for the layer barn than on the other two gas emissions, both with positive correlations.