Estimation of greenhouse gases (N2O, CH4 and CO2) from no-till cropland under increased temperature and altered precipitation regime: a DAYCENT model approach

Divergent regulating modes of greenhouse gas emissions at different soil layers under altered precipitation regime

Simple SummaryMinimizing the effects of climate change by reducing GHG emissions is crucial and can be accomplished by truly understanding the carbon footprint phenomenon. This study aims to improve the understanding of carbon footprint alteration due to agricultural management and fertility practices. It provides a detailed review of carbon footprint management under the impacts of environmental factors, land use, and agricultural practices. The results show that healthy soils have numerous benefits for the general public and especially farmers. These benefits include being stable and resilient, resistant to erosion, easily workable in cultivated systems, good habitat for soil micro-organisms, fertile and good structure, large carbon sinks, and hence lower carbon footprint. Intensive tillage is harmful to soil structure by oxidizing carbon and causing GHG emissions. If possible, no-till; if not, minimum tillage frequency and depth of tillage, and optimum moisture are recommended. The soil should be at an appropriate level of moisture when tillage takes place. Diverse cropping systems are better for the soil than monocultures. Minimizing machinery operations can help to avoid soil compaction. Building soil organic carbon in the most stable form is the most efficient practice of sustainable crop production.Global attention to climate change issues, especially air temperature changes, has drastically increased over the last half-century. Along with population growth, greater surface temperature, and higher greenhouse gas (GHG) emissions, there are growing concerns for ecosystem sustainability and other human existence on earth. The contribution of agriculture to GHG emissions indicates a level of 18% of total GHGs, mainly from carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Thus, minimizing the effects of climate change by reducing GHG emissions is crucial and can be accomplished by truly understanding the carbon footprint (CF) phenomenon. Therefore, the purposes of this study were to improve understanding of CF alteration due to agricultural management and fertility practices. CF is a popular concept in agro-environmental sciences due to its role in the environmental impact assessments related to alternative solutions and global climate change. Soil moisture content, soil temperature, porosity, and water-filled pore space are some of the soil properties directly related to GHG emissions. These properties raise the role of soil structure and soil health in the CF approach. These properties and GHG emissions are also affected by different land-use changes, soil types, and agricultural management practices. Soil management practices globally have the potential to alter atmospheric GHG emissions. Therefore, the relations between photosynthesis and GHG emissions as impacted by agricultural management practices, especially focusing on soil and related systems, must be considered. We conclude that environmental factors, land use, and agricultural practices should be considered in the management of CF when maximizing crop productivity.

Effect of animal manure, crop type, climate zone, and soil attributes on greenhouse gas emissions from agricultural soils—A global meta-analysis

How do sand addition, soil moisture and nutrient status influence greenhouse gas fluxes from drained organic soils?

Two potent greenhouse gases that are mostly found in agricultural soils are methane and nitrous oxide. Therefore, we investigated the effect of different moisture regimes on microbial stoichiometry, enzymatic activity, and greenhouse gas emissions in long-term paddy soils. The treatments included a control (CK; no addition), chemical fertilizer (NPK), and NPK + cattle manure (NPKM) and two moisture regimes such as 60% water-filled pore spaces (WFPS) and flooding. The results revealed that 60% water-filled pore spaces (WFPS) emit higher amounts of N2O than flooded soil, while in the case of CH4 the flooded soil emits more CH4 emission compared to 60% WFPS. At 60% WFPS higher N2O flux values were recorded for control, NPK, and NPKM which are 2.3, 3.1, and 3.5 µg kg−1, respectively. In flooded soil, the CH4 flux emission was higher, and the NPKM treatment recorded the maximum CH4 emissions (3.8 µg kg−1) followed by NPK (3.2 µg kg−1) and CK (1.7 µg kg−1). The dissolved organic carbon (DOC) was increased by 15–27% under all flooded treatments as compared to 60% WPFS treatments. The microbial biomass carbon, nitrogen, and phosphorus (MBC, MBN, and MBP) significantly increased in the flooded treatments by 8–12%, 14–21%, and 4–22%, respectively when compared to 60% WFPS. The urease enzyme was influenced by moisture conditions, and significantly increased by 42–54% in flooded soil compared with 60% WFPS while having little effect on the β-glucosidase (BG) and acid phosphatase (AcP) enzymes. Moreover DOC, MBC, and pH showed a significant positive relationship with cumulative CH4, while DOC showed a significant relationship with cumulative N2O. In the random forest model, soil moisture, MBC, DOC, pH, and enzymatic activities were the most important factors for GHG emissions. The PLS-PM analysis showed that soil properties and enzymes possessed significantly directly impacted on CH4 and N2O emissions, while SMB had indirect positive effect on CH4 and N2O emissions.

Core Ideas Application of urea led to higher N2O emissions than urea–ammonium nitrate in sugarcane. Residue retention led to higher N2O and CH4 emissions irrespective of N source. Both N source and residue management did not affect CO2 emissions. Sugarcane (Saccharum spp.) is a major row‐crop in the southern United States with high rates of N‐fertilizer application and unique harvest‐residue management. A 2‐yr field experiment was conducted to investigate different N‐fertilizer effects (urea and urea ammonium nitrate, UAN) and harvest‐residue managements (residue‐retain, RR, and residue‐burn, RB) on greenhouse gas (GHG) emissions from soils under sugarcane production. In 2012, a split‐plot design experiment was conducted with residue managements as main‐plots and N‐sources as sub‐plots. In 2013, two experiments were conducted to investigate UAN effect under RR and RB, and N‐source effect under RB on GHG emissions. Nitrogen was applied at 135 and 157 kg ha‒1 in 2012 and 2013, respectively. Soil GHG emissions were monitored using a closed chamber method. Results showed the majority of N2O emissions occurred within 4 wk after N‐application. Average N2O emissions from urea‐treated plots were 1.43 to 1.67 times higher compared with UAN for 2 yr. Urea had a N2O emission factor of 3.52 and 4.45% under RB and RR, respectively, whereas UAN had 1.67 and 2.46% under the same residue management. Higher N2O emission under RR treatment was supported by 15 to 20% more water‐filled pore space (WFPS) in soil than RB plots, which also increased CH4 emissions. Higher correlation was found between N2O emission and WFPS in 2012 compared with 2013 (r2 = 0.52 vs. 0.36) because a majority of the rainfall in 2012 was received within 3 wk following N application. Nitrogen sources had no effect on CH4 and CO2 emissions.

The aim of this paper was to compare effects of organic and mineral fertilizers on greenhouse gas (GHG) emissions from legume grasslands in Finland. We invoke DNDC, a process-based model that integrates effects of agricultural practices, soil characteristics, nitrogen mass balance and climate change on GHG emissions from soil-plant ecosystems. Data measured in the field were collected from 2017 to 2020 using an eddy covariance site cultivated with legume grass species (Phleum pratense L., Festuca pratensis Huds, Trifolium pratense L., Hordeum vulgare L.) at Anttila, Maaninka, eastern Finland. The focus of the modelling was to evaluate the performance of DNDC heat exchange version under two distinct management practices: organic input, utilizing digestate residue (slurry), and mineral input (NPK) with chemical fertilizer. The primary emphasis was on understanding the model's accuracy in simulating greenhouse gas emissions and comparing the total annual greenhouse gas exchanges between these two management approaches. The DNDC heat exchange model version was calibrated and validated for key processes, including Gross Primary Productivity (GPP), Net Ecosystem Exchange (NEE), Ecosystem Respiration (Reco), Soil Temperature, and Water-Filled Pore Space (WFPS) at 5 cm and 20 cm depths. The model demonstrated satisfactory performance in estimating the total annual GHG exchanges during validation years under both management practices. For the mineral treatment, the model demonstrated fair performance (Spearman's correlation (ρ) for GPP (0.81), NEE (0.72), and Reco (0.85)). Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values indicated reasonable agreement between model predictions and measured data. Notably, soil temperature simulations demonstrated an excellent correlation (ρ=0.99) with low RMSE and MAE. Water-Filled Pore Space (WFPS) at both 5 cm and 20 cm depths exhibited good correlations, with acceptable RMSE and MAE values. Similarly, for organic inputs, the DNDC model had fair correlation (ρ) for GPP (0.81), NEE (0.72), and Reco (0.85). Soil temperature and WFPS at 5 cm presented high positive correlations (ρ=0.98 and 0.55), accompanied by low RMSE and MAE. WFPS at 20cm, while exhibiting good correlation (ρ=0.065), displayed a slightly elevated RMSE and MAE. Overall, we conclude that the model offered valuable insights into GHG dynamics associated with organic and mineral fertilization practices. Overestimation of biomass yield for some of the data by DNDC suggests that future work would be well placed targeting physiology determinants of biomass in the model.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Microbial removal of C and N in soil-based wastewater treatment involves emission of CO2, CH4, N2O, and N2 to the atmosphere. Water-filled pore space (WFPS) can exert an important control on microbial production and consumption of these gases. We examined the impact of WFPS on emissions of CO2, CH4, N2O, and N2 in soil microcosms receiving septic tank effluent (STE) or effluent from a single-pass sand filter (SFE), with deionized-distilled (DW) water as a control. Incubation of B and C horizon soil for 1 h (the residence time of wastewater in 1 cm of soil) with DW produced the lowest greenhouse gas (GHG) emissions, which varied little with WFPS. In B and C horizon soil amended with SFE emissions of N2O increased linearly with increasing WFPS. Emissions of CO2 from soil amended with STE peaked at WFPS of 0.5–0.8, depending on the soil horizon, whereas in soil amended with SFE, the CO2 flux was detectable only in B horizon soil, where it increased with increasing WFPS. Methane emissions were detectable only for STE, with flux increasing linearly with WFPS in C horizon soil, but no clear pattern was observed with WFPS for B horizon soil. Emissions of GHG from soil were not constrained by the lack of organic C availability in SFE, or by the absence of NO3 availability in STE, and addition of acetate or NO3 resulted in lower emissions in a number of instances. Emission of 15N2 and 15N2O from 15NH4 took place within an hour of contact with soil, and production of 15N2 was much higher than 15N2O. 15N2 emissions were greatest at the lowest WFPS value and diminished markedly as WFPS increased, regardless of water type and soil texture. Our results suggest that the fluxes of CO2, CH4, N2O, and N2 respond differently to WFPS, depending on water type and soil texture.

Application of N fertilizers and special land management practices during agricultural production could have significant implication in influencing the air quality. In this study, field experiments were established at different research sites in Louisiana to evaluate the emission of ammonia (NH3), greenhouse gases (GHG), and fine particulates from sugarcane cultivation and harvesting. Specifically, this study was planned to (i) evaluate the effect of different N sources (urea and urea ammonium nitrate) and residue management schemes (residue burned, RB; and residue retained, RR) on NH3 and GHG emissions, (ii) characterize the chemical and morphological characteristics of fine particles generated during sugarcane harvesting operations (regular harvesting, RH; ground burn, GB; standing burn, SB; and combine harvesting, CH), and (iii) evaluate the micrometeorological study of NH3 flux above sugarcane crop canopy. Ammonia (NH3) and greenhouse gas samples were collected through active and passive chamber methods, respectively, following N application in the field. Then those NH3 and GHG samples were analyzed using ion chromatography (IC) and gas chromatography, respectively. Organic/elemental carbon, water soluble species, elemental species, and morphological features were determined using thermal carbon analyzer, ion chromatography, inductively-coupled plasma-optical emission spectroscopy, and scanning electron microscopy, respectively. Volatile organic carbon and polycyclic aromatic hydrocarbons were analyzed using gas chromatography-mass spectroscopy. Bi-directional NH3 emission was obtained from two installed denuders (at 10 ft and 18 ft) equipped with meteorological tower in the sugarcane field and the captured NH3 was analyzed in IC. Field experiments showed that urea treatment produced almost 2.8 times and 1.6 times higher NH3 and N2O, respectively, as compared to UAN plots. However, N had little effect on CH4 and N2O emissions. Overall, majority of total NH3 and N2O emission was observed within 3-4 weeks after N application in the field. On the other hand, residue retained treatment resulted significantly higher NH3, N2O, and CH4 emissions as compared to RB treatments over the years. Ammonia and N2O emissions were highly correlated with water filled pore space (%), but higher correlation was found in 2012 due to higher rainfall received within 3 weeks of N application. Particulates released during different sugarcane harvesting operations showed that carbonaceous compounds contributed about 30-70% of the total particle mass. Ammonia was the major cation found in the burning particulates (GB and SB) and showed high correlation with SO42- ions. Overall, organic carbon, major ionic species, elemental species were significantly higher in GB particles than SB particles. Low molecular

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Soil structure plays a crucial role in determining greenhouse gas (GHG) emissions from agricultural activities. Changes in soil structure, such as compaction, can alter the factors that govern GHG fluxes, leading to an increased potential for emissions. The extent to which soil compaction explains GHG emissions is still under investigation. To address this knowledge gap, a two-year experiment was conducted in Northeast Italy to examine the influence of soil compaction on GHG emissions. The experimental site comprised of 20 lysimeters representing five different cultivation systems, each with four replicates: bare soil (BS), conventional (CV), conventional + with cover crop (CC), conservation with shallow compaction (0-25 cm, CA1), and conservation with deep soil compaction (25-45 cm, CA2). Maize was cultivated as the main crop in 2022, followed by grain sorghum in 2023, with solid digestate (300 kg N ha-1) originated from mixed agricultural waste used for fertilization. Winter wheat served as a cover crop where necessary. Continuous automatic measurements of CO2, N2O, and CH4 emissions were collected using a non-steady state through-flow chamber system and an FTIR gas analyzer, enabling the capture of up to seven fluxes per day for each replicate. Additionally, water-filled pore space (WFPS) and soil temperature were continuously monitored in the 0-30 cm soil profile using Time Domain Reflectometry (TDR) sensors and thermocouples. Cumulative CO2 reached its peak under CV, followed by CC. Notably, observable N2O emissions were predominantly detected in the two weeks following fertilization with peaks reaching 0.8 kg N-N2O ha-1d-1 under CC, while CA1 and CA2 exhibited lower emissions. Conversely, CH4 emissions were negligible, and the soil primarily acted as a sink. The study provides crucial insights for sustainable agriculture by highlighting the impact of soil compaction on GHG.

IntroductionFarmlands are key sources of greenhouse gas (GHG) emissions, which are susceptible to changes in precipitation regimes. The soils of seasonal fallow contribute approximately half of annual GHG emissions from farmlands, but the effect of precipitation frequency on soil GHG emissions from seasonal fallow croplands remains virtually unknown.Materials and MethodsWe conducted a microcosm study to evaluate the response of nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) fluxes from typical paddy and upland soils to the changes in watering frequency simulating precipitation scenarios of subtropical regions during seasonal fallow. We also analyzed changes of soil properties and biotic characteristics associated with GHG emissions, including abundances of soil denitrifiers (nirK, nirS, nosZI and nosZII genes), methanotrophs (pmoA gene) and methanogens (mcrA gene) to altered watering frequency.ResultsIncreased watering frequency led to overall increases in soil N2O and CO2 fluxes compared with low frequency. Compared with low frequency, high watering frequency decreased CH4 flux from the paddy soil by 3.5 times, while enhanced CH4 flux from the upland soil by 60%. Furthermore, the increased watering frequency had positive effects on cumulative N2O and CO2 fluxes from the upland soil, whereas no similar trend was observed for the paddy soil. Hierarchical partitioning analyses showed that N2O fluxes from the paddy soil were mostly related to nitrogen availability, and mcrA gene abundance had more than 90% of relative independent effects on CH4 and CO2 fluxes from the paddy soil. For the upland soil, nosZ (60.34%), pmoA (53.18%) and nir (47.07%) gene abundances were important predictors of N2O, CH4 and CO2 fluxes, respectively.ConclusionOur results demonstrate that increased watering frequency facilitates GHG emissions by changing soil properties and functional gene abundances. These findings provide new insights into GHG fluxes from seasonal fallow croplands in response to altered precipitation patterns.