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At least 91 records · Page 5

Seasonal nitrous oxide flux from an intensively managed pasture in a humid subtropical ecosystem

Nitrous oxide (N2O) flux from vented chambers was measured over intensively and minimally managed bermuda grass hay meadows in a humid, subtropical ecosystem for several years during scheduled sampling protocol following harvest, fertilization and rainfall events while measuring diel N2O emissions once during each of 5 seasonal day growth cycles which divided each calendar year. Soil pools of nitrite NO2(-), nitrate NO3(-), and ammonia (NH3) were measured in soil samples taken at 2 and 10 cm depths during each emission collection to determine transformations of the nitrogen pools coupled with N2O emissions. The highest diel N2O emission occur midday in the Spring cycle, measuring 9.0 g N/ha/d only for several weeks, while emissions dropped to less than 1.0 g N/ha/day during hot, dry, and colder months. Intensively managed meadows (4 fertilizations and harvests per year plus pest management) induced higher seasonal N2O emissions than minimal treatment (1 fertilization and harvest) averaging 2.75 and 5.97 g N/ha/day. Nitrous oxide emission data as responses to soil parameters and environmental parameters were also measured where air temperature, soil moisture, and fertilization were the most powerful factors.

Brams, Eugene A.↗

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO x ), ammonia (NH 3 ), and nitrous oxide (N 2 O). Here, the propensity of NO x and NH 3 to generate ozone and fine particulate matter (PM) and associated impacts on health are highly variable, whereas the climate impacts of long-lived N 2 O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially-resolved, monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the agricultural emissions of Nr from across the United States. We then apply a reduced-form air pollution health effects model to assess air quality impacts from NO x and NH 3 and a social cost of N 2 O to assess the climate impacts. Assuming an $\$$8.2 million Value of a Statistical Life (VSL) and a $\$$13,100/ton social cost of N 2 O, the air quality impacts are a factor of ~7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

54 ENVIRONMENTAL SCIENCES↗

Influence of shrub willow buffers strategically integrated in an Illinois corn-soybean field on soil health and microbial community composition

We report soil serves many important ecological functions and is an integral part of our existence as a society. However, concerns for soil health are growing globally, in part due to the negative impacts of agricultural management on soil resources. The production of perennial bioenergy crops on marginal land in row-crop production systems is one solution that could improve land-use efficiency and address the sustainability of cropland management. Because the relationship between crop management and the environment is complex, more research is needed to evaluate the potential benefits perennial bioenergy crop production has on soil health, as well as other ecosystem services. In this study, shrub willow buffers were strategically integrated into a corn-soybean cropping system with the main objective of reducing nitrate-N leaching from grain crop production while producing biomass for bioenergy. Two buffer systems (defined by landscape positions) were included for comparison, one on marginal land with exposure to nitrate-N leaching from upslope grain (southern plots) and one on fertile soils with less nitrate-N leaching potential (northern plots). Evaluation of soil (chemistry, bulk density, microbial community) and shrub willow vegetation properties ( fine roots, leaf litter decomposition, and nutrient uptake dynamics), showed that landscape position plays an important role in (1) the dynamics of soil chemical properties, (2) shrub willow's influence and productivity, and (3) the provision of additional ecosystem services such as reductions in nitrous oxide emissions and nitrate-N leaching. In addition, the combination of crop type and landscape position (N-grain, N-willow, S-grain, and S-willow) influenced the species composition of the soil microbial community, resulting in unique and identifiable communities. These results highlight the potential application of shrub willow buffers for ecosystem service provision and support of ecosystem processes; however, understanding the relationship between the microbial community, crop type, and landscape is important for understanding the sustainability of the design.

54 ENVIRONMENTAL SCIENCES↗

Simultaneous field measurements of biogenic emissions of nitric oxide and nitrous oxide

Seasonal and diurnal emissions of NO and N2O from agricultural sites in Jamestown, Virginia and Boulder, Colorado are estimated in terms of soil temperature; percent moisture; and exchangeable nitrate, nitrite, and ammonium concentrations. The techniques and procedures used to analyze the soil parameters are described. The spatial and temporal variability of the NO and N2O emissions is studied. A correlation between NO fluxes in the Virginia sample and nitrate concentration, temperature, and percent moisture is detected, and NO fluxes for the Colorado site correspond with temperature and moisture. It is observed that the N2O emissions are only present when percent moisture approaches or exceeds the field capacity of the soil. The data suggest that NO is produced primarily by nitrification in aerobic soils, and N2O is formed by denitrification in anaerobic soils.

Anderson, Iris Cofman↗

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗

germs-lab/PAPER_miscanthus_soil_response

Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteus (M×g) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N2O) and carbon dioxide (CO2) emissions, as well as key N cycling genes in soils where M×g and maize were grown. A 150-day soil incubation experiment was conducted using soils from a long-term M×g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha−1 year−1) and a contemporary amendment (60 mg N kg−1) with negative control (0 mg N kg−1). We observed significant increases in cumulative N2O emissions in Mxg soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amoA gene abundance, which plays a significant role in nitrification in nutrient-rich soils, also increased with higher legacy fertilization rates in M×g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N2O emissions, but cumulative CO2 emissions and amoA gene abundance significantly increased. The abundances of norB genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N2O emissions, particularly for perennial bioenergy crops.

Lee, Jaejin↗

Role of chemotaxis in the ecology of denitrifiers

It has been recognized that the process of denitrification represents a major sequence in the nitrogen cycle. It involves the anaerobic reduction of nitrate or nitrite to nitrous oxide or elemental nitrogen. This process is responsible for significant losses of nitrogen from agricultural soils. Up to now, little attention has been paid to the ecology of the organisms responsible for denitrification. It is pointed out that chemotaxis would probably offer a strong competitive mechanism for denitrifiers, since chemotaxis would allow denitrifiers to actively reach nitrate by directed motility, rather than by random movement or diffusion of nitrate. The present investigation was initiated to examine the chemotactic responses of several denitrifiers to nitrate and nitrite. Attention is given to bacterial strains, culture media and cell preparation, chemotaxis assays, and competition experiments. It was found that several denitrifiers, including P. aeruginosa, P. fluorescens, and P. Stutzeri, were strongly attracted to NO3(-) and NO2(-).

Kennedy, M. J.↗

Methane and nitrous oxide fluxes in native, fertilized and cultivated grasslands

Measurements of CH4 uptake and N2O emissions in native, nitrogen-fertilized, and wheat-growing prairie soils from spring to late autumn, 1990 are reported. It is found that nitrogen fertilization and cultivation can both decrease CH4 uptake and increase N2O production, thereby contributing to the increasing atmospheric concentrations of these gases.

Mosier, A.↗

Relative rates of nitric oxide and nitrous oxide production by nitrifiers, denitrifiers, and nitrate respirers

An account is given of the atmospheric chemical and photochemical effects of biogenic nitric and nitrous oxide emissions. The magnitude of the biogenic emission of NO is noted to remain uncertain. Possible soil sources of NO and N2O encompass nitrification by autotropic and heterotropic nitrifiers, denitrification by nitrifiers and denitrifiers, nitrate respiration by fermenters, and chemodenitrification. Oxygen availability is the primary determinant of these organisms' relative rates of activity. The characteristics of this major influence are presently investigated in light of the effect of oxygen partial pressure on NO and N2O production by a wide variety of common soil-nitrifying, denitrifying, and nitrate-respiring bacteria under laboratory conditions. The results obtained indicate that aerobic soils are primary sources only when there is sufficient moisture to furnish anaerobic microsites for denitrification.

Anderson, I. C.↗

Lewis acid-assisted reduction of nitrite to nitric and nitrous oxides via the elusive nitrite radical dianion

Reduction of nitrite anions (NO 2 - ) to nitric oxide (NO), nitrous oxide (N 2 O) and ultimately dinitrogen (N 2 ) takes place in a variety of environments, including in the soil as part of the biogeochemical nitrogen cycle and in acidified nuclear waste. Nitrite reduction typically takes place within the coordination sphere of a redox-active transition metal. In this report we show that Lewis acid coordination can substantially modify the reduction potential of this polyoxoanion to allow for its reduction under non-aqueous conditions (-0.74 V versus NHE). Detailed characterization confirms the formation of the borane-capped radical nitrite dianion (NO 2 2- ), which features a N(II) oxidation state. Protonation of the nitrite dianion results in the facile loss of nitric oxide (NO), whereas its reaction with NO results in disproportionation to nitrous oxide (N 2 O) and nitrite (NO 2 - ). This system connects three redox levels in the global nitrogen cycle and provides fundamental insights into the conversion of NO 2 - to NO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗

Bedrock weathering rates, reactive nitrogen influxes and effluxes, and nitrous oxide emissions rates from the Pumphouse Hillslope, East River Watershed, Colorado

Atmospheric nitrous oxide contributes directly to global warming, yet models of the nitrogen cycle do not account for bedrock, the largest pool of terrestrial nitrogen, as a source of nitrous oxide. Although it is known that release rates of nitrogen from bedrock are large, there is an incomplete understanding of the connection between bedrock-hosted nitrogen and atmospheric nitrous oxide. Here, we quantify nitrogen fluxes and mass balances at a hillslope underlain by marine shale. We found that at this site bedrock weathering contributes 78% of the subsurface reactive nitrogen, while atmospheric sources (commonly regarded as the sole sources of reactive nitrogen in pristine environments) account for only the remaining 22%. About 56% of the total subsurface reactive nitrogen denitrifies, including 14% emitted as nitrous oxide. The remaining reactive nitrogen discharges in porewaters to a floodplain where additional denitrification likely occurs. We also found that the release of bedrock nitrogen occurs primarily within the zone of the seasonally fluctuating water table and suggest that the accumulation of nitrate in the vadoes zone, often attributed to fertilization and soil leaching, may also include contributions from weathered nitrogen-rich bedrock. Our hillslope study suggests that under oxygenated and moisture-rich conditions, weathering of deep, nitrogen-rich bedrock makes an important contribution to the nitrogen cycle. The data files are in Excel, which can be accessed using Microsoft Office, and consist of many data sets from the Pumphouse Hillslope PLM (Pumphouse Lower Montane) 1, 2, 3, and 4. They include soil to rock (0-10 meters) solid phase minerals and elements compositions; time- and depth-resolved pore-water chemistry and pore-gas compositions; time- and depth-resolved water table depths and water fluxes; subsurface weathering rates; nitrogen influxes and effluxes and mass balance. The attached paper is in a Word document, which can be accessed using Microsoft Office, and in pdf format.

54 ENVIRONMENTAL SCIENCES↗

The influence of tillage and fertilizer on the flux and source of nitrous oxide with reference to atmospheric variation using laser spectroscopy

Nitrous oxide (N 2 O) is the third most important long-lived greenhouse gas and agriculture is the largest source of N 2 O emissions. Curbing N 2 O emissions requires understanding influences on the flux and sources of N 2 O. We measured flux and evaluated microbial sources of N 2 O using site preference ( S P ; the intramolecular distribution of 15 N in N 2 O) in flux chambers from a grassland tilling and agricultural fertilization experiments and atmosphere. We identified values greater than that of the average atmosphere to reflect nitrification and/or fungal denitrification and those lower than atmosphere as increased denitrification. Our spectroscopic approach was based on an extensive calibration with 18 standards that yielded S P accuracy and reproducibility of 0.7 ‰ and 1.0 ‰, respectively, without preconcentration. Chamber samples from the tilling experiment taken ~ monthly over a year showed a wide range in N 2 O flux (0–1.9 g N 2 O-N ha -1 d -1 ) and S P (- 1.8 to 25.1 ‰). Flux and S P were not influenced by tilling but responded to sampling date. Large fluxes occurred in October and May in no-till when soils were warm and moist and during a spring thaw, an event likely representing release of N 2 O accumulated under snow cover. These high fluxes could not be ascribed to a single microbial process as S P differed among chambers. However, the year-long S P and flux data for no-till showed a slight direct relationship suggesting that nitrification increased with flux. The comparative data in till showed an inverse relationship indicating that high flux events are driven by denitrification. Corn ( Zea mays ) showed high fluxes and S P values indicative of nitrification ~ 4 wk after fertilization with subsequent declines in S P indicating denitrification. Although there was no effect of fertilizer treatment on flux or S P in switchgrass ( Panicum virgatum) , high fluxes occurred ~1 month after fertilization. In both treatments, S P was indicative of denitrification in many instances, but evidence of nitrification/fungal denitrification also prevailed. At 2 m atmospheric N 2 O S P had a range of 31.1 ‰ and 14.6 ‰ in the grassland tilling and agricultural fertilization experiments, respectively. These data suggest the influence of soil microbial processes on atmospheric N 2 O and argue against the use of the global average atmospheric S P in isotopic modeling approaches.

Environmental Sciences & Ecology↗

Quantifying Drivers of Methane Hydrobiogeochemistry in a Tidal River Floodplain System

The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine learning (ML) framework to identify and rank the most influential processes, properties, and conditions controlling methane behavior in a freshwater floodplain responding to recently restored seawater inundation. Our unique multivariate, multiyear, and multi-site dataset comprises tidal creek and floodplain porewater observations encompassing water level, salinity, pH, temperature, dissolved oxygen (DO), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), partial pressure of carbon dioxide (pCO 2 ), nitrous oxide (pN 2 O), methane (pCH 4 ), and the stable isotopic composition of methane (δ 13 CH 4 ). Additionally, we incorporated topographical data, soil porosity, hydraulic conductivity, and water retention parameters for UQ analysis using a previously developed 3D variably saturated flow and transport floodplain model for a physical mechanistic understanding of factors influencing groundwater levels and salinity and, therefore, CH 4 . Principal component analysis revealed that groundwater level and salinity are the most significant predictors of overall biogeochemical variability. The ensemble ML models and UQ analyses identified DO, water level, salinity, and temperature as the most influential factors for porewater methane levels and indicated that approximately 80% of the total variability in hourly water levels and around 60% of the total variability in hourly salinity can be explained by permeability, creek water level, and two van Genuchten water retention function parameters: the air-entry suction parameter α and the pore size distribution parameter m. These findings provide insights on the physicochemical factors in methane behavior in coastal ecosystems and their representation in local- to global-scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗

Chapter 7: Food systems

Food systems - including food production, distribution, consumption, and waste disposal - are critical to sustaining livelihoods and delivering nutrition worldwide. However, food systems contribute significantly to the climate crisis, accounting for over 30 percent of human-caused global greenhouse gas emissions (e.g., methane, carbon dioxide, and nitrous oxide). Climate change, in turn, has a significant and growing impact on food systems. Climate change increases heat stress and can lead to deteriorating soil health, for example, slowing agricultural productivity and reducing the nutritional content of crops and livestock. The cascading impacts of climate extremes on agricultural production are likely to destabilize global food security, endangering the livelihoods of billions of people and threatening public health.

Food systems↗

NitroNet: Smart System to Quantify Nitrous Oxide Emissions

Agricultural croplands are the largest anthropogenic source of nitrous oxide (N 2 O), the third most important greenhouse gas. Emissions are characterized by “hot spots” and “hot moments”, meaning emissions are highly heterogeneous in space and time. Emissions are driven by nitrification and denitrification processes which depend upon complex factors such as soil characteristics (type, compaction, pH, moisture, topography), management practices (fertilizer type and application, tillage, crop type, field history, irrigation), biogeochemistry (organic carbon, microbial composition), and meteorology (precipitation, temperature, and wind). For these reasons, quantifying cropland emissions by either measurements or modeling is extremely challenging with large uncertainties.

09 BIOMASS FUELS↗

Coupled machine learning–ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N 2 O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N 2 O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N 2 O fluxes from US cropland. Trained and validated on ~12,000 N 2 O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N 2 O at both training (R 2 = 0.84, RMSE = 16.4 g N ha −1 d −1 ) and held-out testing sites (R 2 = 0.84, RMSE = 6.2 g N ha −1 d −1 ). Analyses identified six dominant N 2 O drivers: soil organic carbon (SOC), NH 4 + , NO 3 - , water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N 2 O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N 2 O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

AI↗