Organic Nitrogen Substitution Enhances Carbon Sequestration but Increases Greenhouse Gas Emissions in Maize Cropping Systems

Abstract

Excessive chemical fertilizers degrade soil and increase greenhouse gas (GHG) emissions. Organic substitution of nitrogen fertilizers is recognized as a sustainable agricultural-management practice, yet its dual role in carbon sequestration and emissions renders the net GHG balance (NGHGB) uncertain. To assess the GHG mitigation potential of organic substitution strategies, this study analyzed GHG fluxes, soil organic carbon (SOC) dynamics, indirect GHG emissions, and Net Primary Productivity (NPP) based on a long-term field positioning experiment initiated in 2016. Six fertilizer regimes were systematically compared: no fertilizer control (CK); only phosphorus and potassium fertilizer (PK); total chemical fertilizer (NPK); 1/3 chemical N substituted with sheep manure (OF1); dual substitution protocol with 1/6 chemical N substituted by sheep manure and 1/6 substituted by straw-derived N (OF2); complete chemical N substitution with sheep manure (OF3). The results showed that OF1 and OF2 maintained crop yields similar to those under NPK, whereas OF3 reduced yield by over 10%; relative to NPK, OF1, OF2, and OF3 significantly increased SOC sequestration rates by 50.70–149.20%, reduced CH₄ uptake by 7.9–70.63%, increased CO₂ emissions by 1.4–23.9%, decreased N₂O fluxes by 3.6–56.2%, and mitigated indirect GHG emissions from farm inputs by 24.02–63.95%. The NGHGB was highest under OF1, 9.44–23.99% greater than under NPK. These findings demonstrate that partial organic substitution increased carbon sequestration, maintained crop yields, whereas high substitution rates increase the risk of carbon emissions. The study results indicate that substituting 1/3 of chemical nitrogen with sheep manure in maize cropping systems represents an effective fertilizer management approach to simultaneously balance productivity and ecological sustainability.

1. Introduction

Climate change, driven by anthropogenic carbon emissions, presents an urgent global challenge. Agriculture stands as a major contributor, accounting for 22% of global greenhouse gas (GHG) emissions. This sector is responsible for 38% of global methane (CH₄) emissions and 71% of nitrous oxide (N₂O) emissions [1]. As the world’s largest carbon emitter, China contributes 30.6% of global emissions, with its agricultural sector representing 12% of total global agricultural emissions [2]. Fertilizers constitute a major emission source in agriculture, contributing 14% of agricultural GHG emissions [3]. Maize production, being a globally vital crop, frequently involves excessive nitrogen fertilizer application, leading to soil degradation and intensified GHG emissions [3,4]. These challenges are further exacerbated by growing global food demand.

Chemical fertilizers are typically effective in rapidly increasing crop yield and nutrient absorption efficiency. However, long-term and exclusive use may lead to soil acidification, compaction, and a decline in organic matter. In contrast, organic fertilizers (such as cow manure compost and legume green manure) release nutrients more slowly but can significantly improve soil structure [5,6,7], increase organic matter content [8], and promote microbial diversity [9,10]. According to statistics, China produces approximately 1.99 × 10¹² kg of livestock manure and 8.65 × 10¹¹ kg of crop straw annually [11]. Studies have shown that replacing a portion of chemical fertilizers with organic fertilizers can enhance soil organic carbon (SOC), total nitrogen (TN), and available nutrients, thus increasing maize yield in the North China Plain (NCP) [12,13]. For instance, replacing 30% of chemical fertilizers with organic fertilizers has resulted in a significant increase in soil fertility and maize yield [14]. Partial substitution of chemical fertilizers with organic fertilizers is considered an effective strategy to address environmental pollution, food security, and soil degradation [15]. This strategy helps optimize the carbon-to-nitrogen (C/N) ratio, maintaining a balance between crop nitrogen demand and soil supply, reducing nitrogen loss, and increasing SOC storage [15,16,17]. It also stabilizes the soil biological network, further improving crop yield [18,19,20].

While substituting organic fertilizers for chemical nitrogen fertilizers constitutes a sustainable agricultural strategy, their effects on the greenhouse gas (GHG) balance in cropland ecosystems remain debated. The net GHG balance (NGHGB) in agricultural systems is determined by the difference between carbon sequestration and carbon emissions. Carbon sequestration in agroecosystems comprises NPP and changes in soil organic carbon (SOC) stocks, whereas carbon emissions encompass direct soil emissions and indirect emissions from agricultural inputs [18]. Certain studies demonstrate that organic fertilizers supply labile carbon and nutrients, stimulating microbial activity and potentially elevating N₂O emissions [21,22]. Conversely, other research highlights that the elevated carbon-to-nitrogen (C/N) ratio in organic amendments may suppress chemical nitrogen availability, thereby mitigating N₂O emissions [15]. Organic substitution has been demonstrated to increase CO₂ emissions due to exogenous carbon inputs into farmland systems [23], while concurrently enhancing carbon storage through amplified soil carbon inputs and augmented contributions from root exudates and plant litter [24,25]. Furthermore, organic substitution reduces indirect GHG emissions by minimizing chemical fertilizer application, though excessive substitution may impair crop primary productivity due to nutrient availability constraints [26].

To the best of our knowledge, current carbon footprint assessments—often premised on the carbon-neutral assumption of farmland-crop systems—risk underestimating organic fertilizer’s emission impacts by neglecting CO₂ fluxes from agricultural soils and NPP dynamics. Thus, a comprehensive understanding of both carbon storage and carbon emissions under organic substitution is crucial for determining the overall ecological consequences of this management strategy. Compared to previous studies, this research simultaneously considers soil greenhouse gas emissions, soil organic carbon dynamics, net primary productivity (NPP), and the indirect emissions from agricultural inputs under a long-term field experiment. In addition, a systematic study was conducted to quantify the net greenhouse gas balance (NGHGB) of maize production in the semi-arid region of North China under partial substitution scenarios. This research is grounded in a field experiment initiated in 2016, conducted over the period from 2021 to 2022 in North China. The aims were to (1) investigate the dynamics of soil GHG emissions in maize fields under nitrogen fertilizer organic substitution through long-term in situ monitoring; (2) clarify the differential mechanisms of organic nitrogen substitution on soil organic carbon, primary productivity, and indirect carbon emissions from agricultural inputs; (3) quantify NGHGB of maize production through “cradle-to-gate assessment”, identify carbon emission hotspots, evaluate the ecological effects of organic nitrogen substitution, and propose optimization strategies. We hypothesize that partial substitution balances carbon sequestration and emissions better than full substitution.

2. Materials and Methods

2.1. Site Description and Experimental Design

The fertilizer field trial began in 2016 at an experimental farm in Yuquan District of Hohhot, Inner Mongolia, China. (40°45′ N, 111°40′ E, altitude 1040 m). This region has a typical continental climate on the Mongolian Plateau. The average annual precipitation and temperature over the past 30 years have been 404.6 mm and 7.5 °C, respectively. Soils are classified in the Mollisols order and Ustolls suborder according to the USDA soil classification system [27]. The initial physicochemical properties of the surface soil layer in 2016 are shown in Table 1. Maize was the preceding crop. During the study period, the crop growth season rainfall (April to September) was 354.8 mm in 2021 and 255.9 mm in 2022, with a frost-free period of 128–134 days. The actual monthly temperature and precipitation during the maize growing season from 2021 to 2022 are shown in Figure S1.

This study used a one-factor experimental design. with six treatments: no fertilizer control (CK); only phosphorus and potassium fertilizer (PK); total chemical fertilizer (NPK); 1/3 chemical N substituted with sheep manure (OF1); dual substitution protocol with 1/6 chemical N substituted by sheep manure and 1/6 substituted by straw-derived N(OF2); complete chemical N substitution with sheep manure (OF3). Each treatment was repeated thrice, resulting in 18 plots, each covering an area of 100 m². The fertilization rates in this study were based on the recommendations of the local agricultural department: 240 kg N ha⁻¹, 150 kg P₂O₅ ha⁻¹, and 112.5 kg K₂O ha⁻¹. All manure and phosphorus/potassium fertilizers were applied as base fertilizers before sowing. Chemical nitrogen fertilizer was split into base fertilizer and topdressing at a ratio of 1:2, with the topdressing applied at the seven-leaf stage of maize. In the OF2 treatment, straw was shredded and incorporated into the soil in autumn. The physicochemical properties of the organic fertilizer and maize straw used in the experiment are listed in Table 2. The maize variety used was Lihe No. 1, which is commonly cultivated in mid-maturity areas of Inner Mongolia, with 67,500 plants per hectare. Sowing occurred annually on April 28th, with harvesting after maturation around September 28th. The fertilizer dosages for 2021 and 2022 are presented in Table 3.

2.2. Sampling and Analytical Methods

2.2.1. Soil Physicochemical Properties

During the maize maturity stages in 2021 and 2022, the dry matter mass of stems, leaves, husks, cobs, and grains was measured. For each plot, yield was assessed from four rows of 5 m, and the maize yield was standardized to a moisture level of 14%. Post-harvest, soil samples were collected at a depth of 0–20 cm using a soil sampler and a five-point sampling method, which were then mixed thoroughly to obtain representative samples. The soil pH was measured using a pH meter (Mettler-Toledo FE28, Zurich, Switzerland). SOC was determined using the dichromate oxidation method with external heating [28]. Total nitrogen (TN) was measured by the semi-micro Kjeldahl method. Soil ammonium nitrogen (NH₄⁺) and nitrate nitrogen (NO₃⁻) were determined using a continuous flow analyzer (AA3, Seal Analytical Inc., Southampton, UK) [29]. Available phosphorus (AP) was leached with 0.5 mol L⁻¹ NaHCO₃ and quantified using the molybdenum-antimony blue method, while available potassium (AK) was extracted with 1.0 mol L⁻¹ NH₄OAC and determined by flame photometry [30]. Soil bulk density was measured using a soil ring knife method, and soil moisture (SM) was measured using the oven-drying method. Soil temperature (ST) was recorded with a thermometer.

2.2.2. CH₄, CO₂, and N₂O Sampling and Measurement

The soil CH₄, CO₂, and N₂O fluxes during two consecutive years (2021–2022) were measured using the static chamber-gas chromatography method. The upper PVC static chamber (15 cm width × 15 cm length × 30 cm height) was placed into the base frame groove with water-filled channels to ensure airtight sealing, and the base frame was inserted into the topsoil at a depth of 10 cm. Two battery-powered miniature fans are installed at diagonal positions on the top of each chamber to continuously mix the gases, while a thermometer is inserted into the soil within the base to record temperature. A three-way valve and silicone tubing fixed on the chamber sidewall connected to 60 mL medical plastic syringes for gas sampling. Gas collection was conducted daily for 10 consecutive days after tillage and fertilization, followed by weekly sampling intervals during the maize growing season. Four gas samples were collected at 0, 15, 30, and 45 min after chamber closure between 9:00–11:00 a.m. during each sampling event. All samples were injected into 12 mL vacuum vials and transported to the laboratory for analysis using an Agilent 7890B gas chromatograph (Agilent Technologies, Santa Clara, CA, USA) calibrated with high-purity standard gases (0.5 mg L⁻¹). The emission fluxes of CH₄, CO₂, and N₂O were calculated according to the methodology described in Cui et al. (2019) [31].

2.3. Evaluation Metrics and Calculation Methods

2.3.1. System Boundaries

The net GHG balance of the farmland system in this study was defined as the net carbon sequestration minus carbon emissions for each fertilizer treatment throughout the “cradle-to-farm gate” process, expressed in terms of carbon dioxide equivalents (CO₂-eq). Carbon sequestration includes global warming potential (GWP) of NPP (GWP_NPP) and changes in soil organic carbon (GWP_SOC). Carbon emissions encompass the GWP of CH₄, CO₂, and N₂O emissions from soil (GWP_soil), along with the indirect GWP related to agricultural inputs (GWP_input). The agricultural inputs are shown in Figure 1. Notably, manure from livestock systems and returned straw generated within the farmland system were not included in the calculation of the NGHGB [26].

2.3.2. Global Warming Potential of Soil Carbon Emissions (GWP_soil)

GWP_soil represents the combined CO₂ equivalent (CO₂-eq) of cumulative soil CH₄, CO₂, and N₂O emissions and is calculated as follows [23]:

(1)${GWP}_{soil}={CO}_2+{CH}_4\times 29.8+N_{2}O\times 273$

(2)${GWPI}_{soil}={GWP}_{soil}/Yield$

where GWP_soil represents the carbon emission potential due to soil GHG emissions and CO₂, CH₄, and N₂O represent the cumulative emissions measured in the field (kg CO₂·ha⁻¹, kg CH₄·ha⁻¹, and kg N₂O·ha⁻¹, respectively). The global warming potential values for CH₄ and N₂O on a 100-year timescale were 28 and 273, respectively [32].

2.3.3. Global Warming Potential of Agricultural Inputs (GWP_input)

The global warming potential of agricultural inputs (GWP_input) is the sum of the products of the usage of each agricultural input and its corresponding CO₂ emission factor. This emission factor encompasses all stages of crop production, including raw material exploitation, manufacturing, and transportation of the inputs to the field. The agricultural inputs per unit area for each treatment were determined based on the average during the experimental period. The formula for calculating the GHG emissions from these inputs is as follows [33]:

(3)${GWP}_{input}={\sum }_{i=1}^n{I}_{i }\times C_i$

where I_i is the amount of input and C_i is the CO₂ emission factor for each input, as shown in Table 4 and Supplementary Table S1.

2.3.4. Global Warming Potential of Changes in Soil Organic Carbon (GWP_SOC)

The following equation determines the GWP due to changes in SOC storage: GWP_SOC represents the GWP of carbon sink changes (kg CO₂·ha⁻¹·yr⁻¹), which is determined by the following equation [36]:

(4)${GWP}_{SOC}=({S_{final}-S}_{initial})/N\times 44/12$

(5)$S=\sum H_i\times B_i\times {SOC}_i\times \mathrm{10,000}\times 0.001$

S is SOC stock (t C·ha⁻¹), H is soil sampling depth (m), B is soil bulk density (g·cm⁻³), SOC is SOC content (g·kg⁻¹), i represents four soil layers (0–10 cm, 10–20 cm, 20–40 cm, 40–60 cm), 10,000 and 0.001 represented the measurement factors for converting units. S_final refers to the SOC stock at the end of the experiment, and S_initial represents the SOC stock at the beginning of the experiment. N represents the trial duration, and 44/12 is the conversion factor for carbon to CO₂. These data are presented in Table 4.

2.3.5. Global Warming Potential of Net Primary Productivity (GWP_NPP)

GWP_NPP (kg·ha⁻¹) includes the carbon sequestration potential of both aboveground and belowground crop biomass, and the calculation formula is as follows [37]:

(6)${GWP}_{NPP}=0.45\times NPP\times 44/12$

(7)$NPP={NPP}_a+{NPP}_r$

(8)${NPP}_r={NPP}_a\ast 0.06$

where 0.45 is the average carbon content in the crop dry matter. NPP_a represents aboveground biomass (kg·ha⁻¹), NPP_r represents root biomass (kg·ha⁻¹), and 0.06 is the proportion of maize root dry matter to aboveground dry matter at maturity [38].

2.3.6. Net GHG Balance (NGHGB) and Carbon Footprint Calculation

NGHGB (kg CO₂-eq·ha⁻¹) consists of four components, as delineated in Equation (9) [35]. Positive and negative values of NGHGB indicate that the agricultural system functions as a GHG sink and source, respectively.

(9)$NGHGB={GWP}_{NPP}+{GWP}_{SOC}-{GWP}_{soil}-{GWP}_{input}$

Carbon footprint (CF) per unit yield (kg CO₂-eq kg⁻¹) of the cropping system is calculated from five components, as shown in Equation (10) [23]:

(10)$\mathrm{C}\mathrm{F}=({GWP}_{input}+{CH}_4\times 28+N_{2}O\times 273-{GWP}_{SOC})/Yield$

2.4. Statistical Analysis

Data were statistically analyzed using one-way analysis of variance (ANOVA), followed by post-hoc analysis with Duncan’s multiple range test, with a significance threshold set at p < 0.05. Analyses were performed using SPSS version 25.0, and graphs were generated using GraphPad Prism version 5.0.

Partial least squares path modeling (PLS-PM) was used to explore the relationships among soil properties, carbon sequestration, and carbon emissions under conventional nitrogen fertilizer and organic nitrogen substitution regimes. Multicollinearity within the blocks was mitigated by controlling for the variance inflation factor (VIF < 5). The impact of each measured variable on the latent variable of the NGHGB was quantified using factor loadings. The optimal path model was constructed by evaluating all potential paths, with path coefficients indicating the direction and magnitude of the linear relationships between the latent variables. The coefficient of determination (R²) was used to represent the proportion of the variance explained for each observed variable. PLS-PM analysis was performed using the “plspm” package in R version 3.6.1 (R Core Team, 2020).

3. Results

3.1. Farmland Soil GHG Emissions

The fertilization treatments exhibited similar trends in CH₄ fluxes, all of which showed negative cumulative emissions (Figure 2). In 2021, following a transient peak on June 2nd, CH₄ emission fluxes rapidly declined to net uptake status across treatments. All treatments, except for OF3 and PK, maintained relatively high CH₄ uptake rates until early July. NPK demonstrated the highest CH₄ uptake capacity, while OF3 showed the lowest. Compared with NPK, the cumulative CH₄ uptake of OF1, OF2, and OF3 decreased significantly by 33.51%, 39.16%, and 70.63%, respectively. In 2022, CH₄ emission fluxes displayed smoother temporal dynamics than in 2021. The descending order of cumulative CH₄ uptake was as follows: NPK > OF1 > OF2 > CK > OF3 > PK.

As shown in Figure 3, CO₂ emission fluxes peaked on 6 June 2021, across all treatments, while they exhibited relatively smooth variations in 2022. The cumulative emissions from the OF3 treatment remained the highest in both consecutive years (27.12–33.58 t CO₂-eq ha⁻¹), significantly exceeding those of the NPK treatment by 12.7–23.9% (p < 0.05). No significant differences were observed among the partial organic substitution treatments (OF1 and OF2) and conventional NPK fertilization. The nitrogen-applied treatments showed significantly higher cumulative CO₂ emissions than the non-nitrogen treatments (p < 0.05).

N₂O emission fluxes exhibited consistent patterns across both years. Distinct emission peaks occurred in all nitrogen-applied treatments following basal and topdressing fertilization events (Figure 4). The OF3 treatment demonstrated the highest flux after basal fertilization, while NPK, OF1, and OF2 showed significant increases after topdressing. The NPK treatment yielded the highest cumulative N₂O emissions, exceeding the control (CK) by 391.54–445.42% (p < 0.05). Compared with NPK, the N₂O mitigation efficiencies of OF1, OF2, and OF3 were 3.62–38.44%, 24.96–56.25% (p < 0.05), and 19.60–20.07% (p < 0.05), respectively.

Regarding maize yield, partial organic substitution maintained equivalent crop productivity under NPK, with the OF1 regime marginally increasing the yield by 2.18–2.27% compared to NPK (p > 0.05) (Table 5). In contrast, OF3 resulted in a significant yield reduction of 10.6–11.1% (p < 0.05). An aggregate GHG emissions analysis revealed that OF3 demonstrated a substantially greater environmental impact, with total emissions increasing by 10.9–36.2% (p < 0.05) and emission intensity rising by 12.8–40.0% (p < 0.05) versus conventional NPK fertilization. The partial organic substitution treatments (OF1 and OF2) demonstrated non-significant differences from NPK in terms of both total GHG emissions and emission intensity.

3.2. Soil Organic Carbon

The effects of fertilization on the SOC content and soil carbon sequestration rate are shown in Table 6. Compared to the control (CK), organic fertilizer substitution significantly increased the SOC content in the 0–10 cm soil layer, with the OF3 treatment showing a notable increase of 17.46–18.56% (p < 0.05). The magnitude of SOC enhancement exhibited a decreasing trend with an increasing soil depth. Relative to conventional chemical fertilization (NPK), organic substitution increased the SOC content across soil layers, particularly in the 0–20 cm surface layer, where the OF3 treatment resulted in a significant 6.19–13.86% elevation compared to NPK (p < 0.05). Furthermore, organic substitution significantly enhanced soil carbon sequestration rates by 50.70–149.20% (p < 0.05) compared to NPK, with OF3 achieving the highest rate at 1.41–1.57 t C ha⁻¹.

3.3. Indirect Carbon Emissions from Agricultural Inputs

The indirect emissions from agricultural inputs for the different fertilizer treatments and the contribution rates of each factor are shown in Figure 5. NPK had the highest indirect GHG emissions, reaching 2.77 t CO_2-eq·ha⁻¹. Compared to NPK, the CK, OF1, OF2, OF3, and PK treatments reduced emissions by 65.81%, 25.07%, 24.02%, 63.95%, and 52.43%, respectively (Figure 5A). Among the treatments involving chemical nitrogen fertilizer, fertilizers and electricity acted as primary contributors, representing 35–42% and 24–31% of the total indirect emissions, respectively. In contrast, for the treatments without chemical nitrogen fertilizer, electricity and fossil fuels were the main contributors, accounting for from 44% to 55% and from 27% to 34% of the emissions, respectively (Figure 5B).

3.4. Net Primary Productivity Carbon Sequestration in Maize

To comprehensively investigate the carbon balance in farmlands under organic substitution, carbon sequestration in maize under different fertilizer treatments was measured over two consecutive years (Figure 6). Over the two-year period, the carbon sequestration of each organ was ranked. The OF1 treatment achieved the highest carbon sequestration, with values of 14.21 t/ha and 11.89 t/ha in 2021 and 2022, respectively. However, these values did not significantly differ from those of the other nitrogen fertilizer treatments.

3.5. Net GHG Balance and Carbon Footprint in Farmland

The NGHGB in maize agroecosystems is regulated by the bidirectional processes of carbon sequestration and carbon emissions (Table 7). Farmland carbon sequestration includes net primary productivity and soil SOC increment. OF1 had the highest net primary productivity carbon sequestration, which was significantly higher than that of the CK but not significantly different from that of the other nitrogen treatments. Changes in SOC were the highest in OF3, and they were significantly greater than in the other treatments. Farmland carbon emissions include total soil GHG emissions and indirect carbon emissions from agricultural inputs. Carbon emissions due to soil GHG emissions accounted for 88.64–96.33%, with OF3 showing the highest emissions. Nitrogen substitution reduced indirect emissions from agricultural inputs, with OF3 achieving the lowest level (63.84% lower than NPK). Among treatments, OF1 exhibited the highest absolute NGHGB, indicating the strongest net carbon sink capacity. Specifically, its NGHGB was from 111.66% to 175.48% higher than CK (p < 0.05) and from 9.44% to 23.99% higher than NPK (p > 0.05). The carbon footprint of farmland was consistently lowest under the OF3 treatment over the two consecutive years, while the PK treatment exhibited the highest carbon footprint based on the two-year average data.

3.6. Relationships Between Net GHG Balance and Soil Properties

PLS-PM was employed to identify the relationships among the farmland NGHGB, the global warming potential of total farmland carbon sequestration (GWP_TCS), the global warming potential of total farmland carbon emissions (GWP_TCE), soil physical environment, soil nitrogen, and SOC (Figure 7A,B). Under conventional nitrogen fertilizer, soil nitrogen had a considerable positive direct influence on SOC (path coefficient = 0.678, p < 0.01) and total farmland carbon sequestration (path coefficient = 0.641, p < 0.001). Total farmland carbon sequestration significantly positively affected the NGHGB (path coefficient = 0.574, p < 0.01). Under partial organic nitrogen substitution, soil nitrogen had a markedly stronger positive direct effect on SOC (path coefficient = 0.803, p < 0.001), total farmland carbon sequestration (path coefficient = 0.759, p < 0.01), and total farmland carbon emissions (path coefficient = 0.539, p < 0.01). Total farmland carbon sequestration had a significant positive direct effect on the NGHGB (path coefficient = 0.907, p < 0.01), whereas total carbon emissions had a pronounced negative direct effect on the NGHGB (path coefficient = −0.852, p < 0.01). Compared to NPK, partial organic substitution had higher path coefficients for both total carbon emissions and total carbon sequestration in regulating the farmland NGHGB, suggesting a more pronounced role of partial organic substitution in regulating farmland GHG dynamics. The standardized total effects (Figure 7C,D) revealed the influence of soil nitrogen, SOC, soil physical environment, total farmland carbon sequestration, and total farmland carbon emissions on the NGHGB of farmlands. Figure S2 and Table S2 present the soil physicochemical properties under different fertilizer treatments. Figure S3 shows that CH₄, CO₂, and N₂O emissions were significantly positively correlated with SOC, SM, and ST, whereas N₂O emissions were significantly correlated with NN and AN. In addition, TN and SOC were significantly positively correlated.

4. Discussion

4.1. Impact of Organic Nitrogen Fertilizer Substitution on Farmland Carbon Sequestration

Farmland carbon sequestration includes carbon fixation through crop primary productivity and changes in soil organic carbon storage. The research results indicate that, compared to NPK fertilization, partial organic fertilizer substitution showed no significant difference in net primary productivity, with OF1 even exhibiting a slight increase.

Another global review found that long-term application of organic fertilizers increased SOC content by 23–49% [9]. A meta-analysis indicated that replacing mineral nitrogen fertilizers with livestock manure could increase crop yield by 4.4% and enhance carbon sequestration by 33% [39], which is similar to the findings of this study. This might be attributed to sheep manure providing high-quality carbon components and active microbial communities that promote nutrient release and improve nutrient use efficiency. Organic substitution can stimulate soil microbial growth and mineralization [40,41], aligning nitrogen demand with nutrient supply to ensure that both long-term nitrogen availability and short-term nutrient requirements are met, thereby promoting crop growth and enhancing carbon sequestration through net primary productivity [42]. However, complete substitution significantly reduced maize yield and net primary productivity, likely due to the fact that, under full organic substitution, nitrogen predominantly exists in organic forms, which must undergo mineralization to inorganic nitrogen for plant uptake—a process that is typically slow and highly dependent on environmental factors. Maize requires over 60% of its total nitrogen demand during the jointing to tasseling stages. The slow nutrient release kinetics cannot meet the crop’s nutritional needs during this critical growth window, which affects ear differentiation and grain formation. This ultimately results in significantly lower maize yield and net primary productivity compared to both conventional fertilization and partial nitrogen substitution regimes [18,40]. In addition to slow nitrogen mineralization, other factors such as changes in soil pH and microbial competition may also contribute to the yield reduction. For example, the relatively high carbon-to-nitrogen (C/N) ratio in organic amendments may lead to nitrogen fixation in the soil, further limiting nitrogen availability. To mitigate these agronomic constraints, synchronizing nutrient release with crop demand is crucial. Future research could explore methods such as controlled-release fertilizers or integrating other organic amendments, which could better align nutrient supply with crop needs, thus optimizing yield and nutrient efficiency [43,44].

Organic substitution increased SOC concentration, with the highest SOC sequestration rate observed under full organic substitution, and the increase was concentrated in the 0–20 cm soil layer. This is because organic fertilizer application directly enhances SOC through external organic carbon inputs [45,46]. A comprehensive global review demonstrated that organic fertilizer application increased SOC stocks by 7.41 Mg C ha⁻¹ compared to chemical fertilizers, with approximately 72% of this increase attributed to the direct contribution of organic fertilizer inputs [47]. Additionally, organic substitution improved nutrient availability and elevated soil nitrogen components [48], thereby indirectly promoting SOC accumulation through increased plant carbon inputs [49]. It is important to note that accelerated saturation from long-term high levels of organic fertilizer input may lead to reduced carbon retention efficiency [50]. Experimental studies have shown that after 10 years of continuous organic fertilizer application, the soil retention rate of newly input carbon dropped from an initial 35% to 12% [51,52]. Therefore, the long-term goal of organic substitution should shift from “increasing carbon stocks” to “maintaining the stability and function of the carbon pool,” to avoid emission rebound caused by the blind pursuit of high carbon storage.

4.2. Impact of Organic Nitrogen Fertilizer Substitution on Farmland Carbon Emissions

In this study, farmland carbon emissions encompass both direct soil greenhouse gas emissions and indirect carbon emissions from agricultural inputs. Well-aerated upland soils generally act as methane sinks, with methanotrophs (microorganisms that utilize methane as an energy source) oxidizing methane to carbon dioxide (CO₂), thereby reducing soil methane concentrations [53]. In this study, OF3 resulted in the lowest methane uptake, likely due to increased CH₄ emissions during organic matter decomposition. Conversely, chemical fertilizer application slightly increased methane uptake, which aligns with the nutrient limitation hypothesis [54]. This hypothesis posits that the nutrient present in the lowest supply to the soil is the limiting nutrient. When this limiting element, nitrogen, is added, methane oxidation increases until a saturation point is reached. This also explains the lower methane uptake observed in the PK treatment group.

The substitution of organic materials resulted in higher CO₂ emissions from farmlands, primarily as a result of the decomposition of organic matter. Previous studies have observed that the incorporation of organic matter into maize cultivation practices results in increased CO₂ emissions [20]. Shakoor performed a global meta-analysis, which demonstrated that the application of organic fertilizers derived from manure resulted in an increase in GHG emissions from agricultural lands [55]. Applying organic fertilizers enhances various biological enzymes and nutrient availability, activates microorganisms, and thus accelerates CO₂ production [56,57]. In our study, we observed a rising trend in farmland CO₂ emissions contingent upon the increase in organic nitrogen substitution, consistent with previous studies [58].

The N₂O within soils is generated via nitrification and denitrification processes, wherein nitrate nitrogen (NO₃⁻) and ammonium nitrogen (NH₄⁺) serve as substrates [59]. Chemical nitrogen fertilizers are the primary source of N₂O emissions from agricultural soils [60,61], as fertilizer type affects N₂O emissions by influencing nitrogen availability in the soil. In this study, the highest N₂O emissions were observed under NPK, which can be attributed to the significantly higher nitrate and ammonium nitrogen levels (Table S2), which serve as precursors for rapid N₂O production through microbial nitrification and denitrification [62,63]. In contrast, the organic nitrogen provided by organic fertilizers requires a longer mineralization period [64,65], resulting in lower N₂O emissions in the organic substitution treatments than in NPK. Organic fertilizer application can also enhance electron flow through denitrification in soils with low NO₃⁻ concentrations, promoting the conversion of N₂O to N₂, thereby reducing N₂O emissions [66,67,68]. Among the organic substitution treatments, OF2 had the lowest N₂O emissions; this is possibly because it included one-sixth of the straw nitrogen, resulting in a higher overall C ratio, which led to the microbial utilization of soil nitrogen sources, thereby limiting nitrification and denitrification processes and reducing N₂O production.

Although all treatments maintained negative CH₄ fluxes, indicating that the maize fields acted as a net CH₄ sink, the overall climate benefit from methane uptake was relatively small. This is due to the lower radiative forcing of CH₄ (GWP₁₀₀ = 28) and its limited flux magnitude compared to the substantial increases in N₂O emissions (GWP₁₀₀ = 273) under high organic nitrogen inputs, especially in the OF3 treatment. Under treatments with high organic input (e.g., OF3), the increase in N₂O emissions more than offsets the climate benefit of CH₄ uptake, leading to a net increase in greenhouse gas emissions. Conversely, partial substitution scenarios (e.g., OF1) maintained CH₄ uptake while keeping N₂O emissions at relatively lower levels, contributing to a more favorable net GHG balance. These findings underscore the importance of balancing nitrogen input levels to optimize mitigation outcomes.

Noteworthily, when studying the indirect carbon emissions from agricultural inputs, sheep manure—derived from livestock system waste—was not included in the indirect carbon emission assessment of agricultural inputs [26]. Among all fertilization treatments, the NPK treatment exhibited the highest indirect carbon emissions from agricultural inputs. Compared to NPK, organic nitrogen fertilizer substitution reduced indirect carbon emissions by 24–63%, with higher substitution rates leading to lower indirect GHG emissions. This phenomenon can be attributed to two key factors: (1) the substantial nitrogen fertilizer input and elevated emission factors in maize production systems [31], and (2) the exclusion of sheep manure—derived from livestock system waste—from the indirect carbon emission assessment of agricultural inputs [26].

4.3. Impact of Organic Nitrogen Fertilizer Substitution on the NGHGB

In this study, we evaluated the ecological effects of organic substitution in farmland systems using the NGHGB. A positive value indicates that the farmland ecosystem acts as a GHG sink, while a negative value signifies a GHG source [69]. The NGHGB is collectively influenced by four factors: carbon sequestration potential from net primary productivity, soil organic carbon (SOC) change potential, soil GHG emission potential, and the indirect warming potential of agricultural inputs. This study demonstrated that substituting one-third of the chemical fertilizers with sheep manure enhanced crop productivity and net primary productivity carbon sinks, primarily by improving nutrient availability and soil quality [6]. Regarding GHG emissions, although organic substitution reduced N₂O emissions, it increased CO₂ emissions, leading to a slight overall rise in GHG emissions. Organic substitution significantly reduced indirect carbon emissions from agricultural inputs due to decreased fertilizer use. Simultaneously, it substantially increased SOC sequestration through external carbon inputs, achieving a synergistic enhancement of carbon sequestration and crop yield.

Meanwhile, we also found that assessing the carbon effects of organic fertilizer application using the carbon footprint methodology has certain limitations. This is because, compared to conventional chemical fertilizer application, organic fertilizers significantly stimulate CO₂ emissions from farmland soils, and excessive organic substitution leads to a notable reduction in carbon sequestration from primary productivity. Therefore, evaluating the carbon footprint of organic fertilizers by treating the farmland system as carbon-neutral is incomplete. Incorporating measurements of soil CO₂ emissions and carbon sequestration from farmland primary productivity would enable a more systematic and comprehensive assessment of the carbon sequestration effects of organic fertilizer application.

4.4. Uncertainties and Limitations

The conclusions of this study may be influenced by several uncertainties: (1) Although organic substitution significantly reduced indirect carbon emissions from agricultural inputs (24–63%), the exclusion of upstream carbon emissions associated with sheep manure (e.g., composting and transportation) from the assessment framework may have led to a systematic overestimation of the net emission reduction benefits. Future studies should adopt a life cycle assessment (LCA) to integrate coupled carbon emissions from livestock and farmland systems. (2) The soil type in this study was chestnut soil with a low organic matter content, and the experimental duration was less than 10 years, which did not trigger the saturation effect of soil organic carbon (SOC) pools [70], resulting in a relatively high carbon sequestration rate under organic substitution. These findings may be constrained by soil type and regional environmental conditions. (3) The indirect emission calculations for agricultural inputs in this study relied on literature-derived emission factors from the same eco-type regions without calibration based on region-specific actual conditions [34,35], potentially leading to partial deviations between the calculated results and actual values. (4) This study lacks an assessment of the actual mineralization rate of straw-derived nitrogen in the OF2 treatment. Although we acknowledge that straw is an important source of organic matter that can enhance nitrogen availability in the soil, the mineralization process is complex and influenced by various factors, such as soil temperature, moisture, and microbial activity. In this study, we did not directly measure the mineralization rate of straw-derived nitrogen. Future research could employ methods such as isotope labeling to accurately assess its contribution to soil nitrogen dynamics and its impact on crop growth and nitrogen management.

5. Conclusions

In the maize cropping systems of the semi-arid region of Northern China, replacing one-third of the chemical nitrogen fertilizer with sheep manure effectively enhanced net primary productivity (NPP) and soil organic carbon (SOC) stocks, reduced indirect carbon emissions from agricultural inputs, and significantly improved the net greenhouse gas balance (NGHGB) of farmland systems while maintaining maize yield. In this study, the impact of partial organic substitution on farmland carbon balance was systematically quantified, providing scientific evidence and practical guidance for promoting green and low-carbon agricultural transformation and achieving China’s “dual carbon” goals. Future research should further assess the adaptability and long-term environmental effects of different types and substitution ratios of organic fertilizers across diverse agroecosystems in order to optimize more widely applicable sustainable fertilization strategies.

Author Contributions

Z.L., F.S., X.Z. (Xiangqian Zhang) and Y.L. designed the experiments. Y.L., X.Z. (Xiaoqing Zhao), R.X., T.M., Y.C., L.C. and Y.R. carried out the experiments. Y.L., C.X., K.Z., S.W. and J.F. analyzed the experimental results. Y.L. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The original contributions presented in this study are included in this article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1 The boundary line of this study.

Figure 2 CH₄ emission fluxes and cumulative values under different treatments. (A,B) and (C,D) illustrate soil CH₄ emission rates and growing-season cumulative emissions for 2021 and 2022, respectively. Black arrows indicate fertilization timings. Different letters within the same column indicate significant differences among fertilization treatments at the p < 0.05 level (one-way ANOVA).

Figure 3 CO₂ emission fluxes and cumulative emissions of different treatments. (A,B) and (C,D) illustrate soil CO₂ emission rates and growing-season cumulative emissions for 2021 and 2022, respectively. Black arrows indicate fertilization timings. Different letters within the same column indicate significant differences among fertilization treatments at the p < 0.05 level (one-way ANOVA).

Figure 4 N₂O emission fluxes and cumulative emissions of different treatments. (A,B) and (C,D) illustrate soil N₂O emission rates and growing-season cumulative emissions for 2021 and 2022, respectively. Black arrows indicate fertilization timings. Different letters within the same column indicate significant differences among fertilization treatments at the p < 0.05 (one-way ANOVA).

Figure 5 Indirect carbon emissions from agricultural inputs and the contribution of different factors under different fertilization treatments. (A) is the indirect carbon emissions from agricultural inputs under different fertilization treatments, while (B) represents the contribution rates of various factors.

Figure 6 Carbon sequestration of different maize organs at maturity under different fertilization treatments. Different letters within the same column indicate significant differences among fertilization treatments at p < 0.05 (one-way ANOVA).

Figure 7 Partial least squares path modeling (PLS-PM): (A) full nitrogen fertilizer treatment; (B) organic fertilizer substitution for nitrogen fertilizer treatment. Standardized total effects (STEs): (C) full nitrogen fertilizer treatment; (D) organic fertilizer substitution for nitrogen fertilizer treatment. Each box in A and B represents an observed variable or a latent variable. Soil nitrogen is a latent variable, including total soil nitrogen, nitrate nitrogen, and ammonium nitrogen; soil organic carbon is a latent variable; soil physical properties is a latent variable, including soil moisture (%) and soil temperature (°C); total carbon sequestration (TCS) in farmland is a latent variable, including primary productivity carbon sequestration and changes in soil organic carbon; total carbon emissions (TCEs) in farmland is a latent variable, including total soil GHG emissions and indirect carbon emissions from agricultural inputs; and the NGHGB in farmland is an observed variable. Larger path coefficients are reflected by the width of the arrows, with red solid lines indicating significant positive effects, blue solid lines indicating significant negative effects, and gray lines indicating insignificant effects. * p < 0.05; ** p < 0.01; *** p < 0.001.

Table 1

The initial physicochemical properties of the surface soil (0–20 cm) layer in 2016.

Year	SOC(g·kg−1)	Total N (g·kg−1)	Total Phosphorus (g·kg−1)	Total Potassium (g·kg−1)	Available Phosphorus (mg·kg−1)	Available Potassium (mg·kg−1)	pH
2016	14.57	1.18	0.91	23.21	15.70	163.00	7.58

Table 2

Physicochemical properties of sheep manure in 2021–2022.

Year	Sheep Manure				Maize Straw
	Moisture Content (%)	Total N (g·kg−1)	Total P (g·kg−1)	Total K (g·kg−1)	Total N (g·kg−1)	Total P (g·kg−1)	Total K (g·kg−1)
2021	35.75	13.6	15.1	16.2	7.1	3.9	13.4
2022	42.61	15.1	14.4	17.6	8.3	3.1	12.2

Table 3

Input of N, P, and K (kg ha⁻¹) under different treatments in 2021–2022.

Year	Treatment	Organic Fertilizer			Chemical Fertilizer
		N	P	K	N	P	K
2021	CK	0	0	0	0	0	0
	NPK	0	0	0	240	150	112.5
	OF1	80	87.1	94.1	160	62.9	18.39
	OF2	80	65.5	122.5	160	84.5	0
	OF3	240	266.5	285.9	0	0	0
	PK	0	0	0	0	150	112.5
2022	CK	0	0	0	0	0	0
	NPK	0	0	0	240	150	112.5
	OF1	80	76.3	93.2	160	73.7	19.3
	OF2	80	53	105.4	160	97	7.1
	OF3	240	228.9	279.7	0	0	0
	PK	0	0	0	0	150	112.5

Note: CK is no fertilizer, NPK is chemical fertilizer, OF1 is 1/3 nitrogen fertilizer substitution by sheep manure, OF2 is 1/3 nitrogen fertilizer substitution by 1/6 sheep manure and 1/6 straw nitrogen, OF3 is complete chemical nitrogen fertilizer substitution by sheep manure, PK is only phosphorus and potassium fertilizer.

Table 4

The GHG emission factors for producing and transporting various agricultural inputs in the maize production system.

Items	Factors	Units	Reference
N fertilizer (N)	7.76	kg CO2-eq kg−1	Chen et al., 2015 [34]
P fertilizer (P2O5)	2.33	kg CO2-eq kg−1	Chen et al., 2015 [34]
Potash fertilizer (K2O)	0.66	kg CO2-eq kg−1	Chen et al., 2015 [34]
Diesel fuel	3.32	kg CO2-eq kg−1	Liu et al., 2013 [35]
Electricity for irrigation	0.92	kg CO2-eq kW·h−1	Liu et al., 2013 [35]
Pesticide	6.58	kg CO2-eq kg−1	Liu et al., 2013 [35]
Labor	0.68	kg CO2-eq person−1 d−1	Liu et al., 2013 [35]
Seeds: Maize	1.22	kg CO2-eq kg−1	Liu et al., 2013 [35]

Table 5

Maize yield, cumulative GHG emissions, and emission intensity under different treatments.

Time	Treatment	Yield (t·ha−1)	N2O(kg CO2-eq·ha−1)	CH4(kg CO2-eq·ha−1)	CO2(t CO2-eq·ha−1)	GWPsoil(t CO2-eq·ha−1)	GWPsoil Intensity(t CO2-eq·t−1)
2021	CK	10.72 ± 0.25 c	285.52 ± 17.15 d	−16.57 ± 0.84 b	23.44 ± 1.59 d	23.71 ± 1.6 c	2.21 ± 0.31 ab
	NPK	14.95 ± 0.26 a	1403.45 ± 113.9 a	−24.92 ± 1.84 a	27.1 ± 0.39 c	28.48 ± 0.5 b	1.91 ± 0.24 c
	OF1	15.29 ± 0.89 a	1352.61 ± 140.6 ab	−16.31 ± 1.72 b	29.72 ± 2.86 ab	31.06 ± 1.87 ab	2.07 ± 0.18 b
	OF2	14.82 ± 0.21 a	1053.05 ± 80.61 c	−12.85 ± 1.44 bc	27.35 ± 0.97 bc	28.4 ± 1.05 b	1.92 ± 0.26 c
	OF3	13.29 ± 0.62 b	1121.76 ± 132.9 b	−4.57 ± 0.56 d	33.58 ± 2.81 a	34.7 ± 2.14 a	2.61 ± 0.22 a
	PK	11.05 ± 0.67 c	234.05 ± 52.89 d	−9.15 ± 0.84 cd	22.55 ± 0.96 d	22.7 ± 1.01 c	2.05 ± 0.15 b
	F-values	45.04	39.72	16.41	11.79	11.80	6.67
2022	CK	10.32 ± 0.5 c	262.8 ± 71.13 d	−14.61 ± 0.44 b	20.66 ± 1.48 c	20.91 ± 0.88 c	2.03 ± 0.17 a
	NPK	14.19 ± 1.22 a	1433.37 ± 129.9 a	−19.39 ± 1.4 a	24.06 ± 0.68 b	25.46 ± 1.21 b	1.80 ± 0.22 b
	OF1	14.5 ± 0.24 a	882.31 ± 126.4 b	−18.27 ± 0.6 a	24.47 ± 0.75 b	25.33 ± 0.87 b	1.75 ± 0.2 b
	OF2	13.98 ± 1.24 a	627.06 ± 74.3 c	−18.47 ± 0.96 a	24.41 ± 1.16 b	25.02 ± 1.43 b	1.79 ± 0.19 b
	OF3	12.69 ± 0.88 b	1152.37 ± 103.2 b	−13.29 ± 0.48 b	27.12 ± 1.22 a	28.27 ± 1.19 a	2.23 ± 0.23 a
	PK	10.73 ± 0.14 c	319.8 ± 164.5 d	−9.4 ± 0.56 c	19.99 ± 1.12 c	20.97 ± 1.28 c	1.95 ± 0.29 ab
	F-values	28.43	50.78	10.27	19.11	19.04	3.49

Note: Data are the means of the three replicates presented as means ± SD. Different letters within the same column indicate significant differences among fertilizer treatments at the p < 0.05 level (one-way ANOVA).

Table 6

Soil organic carbon, bulk density (BD), and soil carbon sequestration in the 0–60 cm layer before and after the experiment.

Year	Item	SOC (g/kg)				BD (g/cm3)				Carbon Sequestration Rate
										(kg·CO2·ha−1·yr−1)
		0–10 cm	10–20 cm	20–40 cm	40–60 cm	0–10 cm	10–20 cm	20–40 cm	40–60 cm	0–60 cm
2016	Basic data	14.57 ± 0.75	14.25 ± 0.62	12.44 ± 0.22	10.15 ± 0.82	1.36 ± 0.07	1.39 ± 0.12	1.52 ± 0.17	1.43 ± 0.12	---
2021	CK	13.96 ± 0.62 c	14.09 ± 1.01 b	12.35 ± 0.41 b	9.67 ± 0.52 a	1.34 ± 0.10 a	1.40 ± 0.13 a	1.51 ± 0.12 a	1.41 ± 0.14 a	−0.20 ± 0.03 d
	NPK	14.67 ± 0.54 bc	14.46 ± 0.47 b	12.47 ± 0.54 ab	10.72 ± 0.34 a	1.40 ± 0.09 a	1.42 ± 0.14 a	1.52 ± 0.11 a	1.34 ± 0.15 a	0.63 ± 0.12 c
	OF1	15.38 ± 0.91 ab	15.15 ± 0.68 ab	13.25 ± 0.64 ab	10.47 ± 0.36 a	1.34 ± 0.11 a	1.46 ± 0.11 a	1.51 ± 0.14 a	1.41 ± 0.17 a	1.15 ± 0.14 b
	OF2	15.27 ± 1.14 ab	15.08 ± 0.72 ab	13.03 ± 0.82 ab	10.54 ± 0.28 a	1.33 ± 0.139 a	1.35 ± 0.12 a	1.53 ± 0.16	1.45 ± 0.17 a	1.13 ± 0.09 b
	OF3	16.55 ± 1.26 a	16.35 ± 0.94 a	13.29 ± 0.37 a	10.61 ± 0.66 a	1.29 ± 0.12 a	1.33 ± 0.12 a	1.47 ± 0.13 a	1.33 ± 0.14 a	1.57 ± 0.13 a
	PK	13.79 ± 0.64 c	13.57 ± 0.75 b	12.26 ± 0.31 b	10.22 ± 0.32 a	1.41 ± 0.13 a	1.43 ± 0.14 a	1.53 ± 0.17 a	1.39 ± 0.11 a	−0.09 ± 0.02 d
2022	CK	14.26 ± 0.51 c	14.01 ± 0.83 b	12.11 ± 0.34 b	10.20 ± 0.47 a	1.34 ± 0.12 a	1.41 ± 0.08 a	1.56 ± 0.22 a	1.41 ± 0.16 a	−0.40 ± 0.05 c
	NPK	14.71 ± 0.63 bc	14.55 ± 0.32 b	12.56 ± 0.63 ab	10.22 ± 0.19 a	1.39 ± 0.11 a	1.40 ± 0.15 a	1.51 ± 0.09 a	1.42 ± 0.21 a	0.71 ± 0.16 b
	OF1	15.20 ± 1.1 b	14.66 ± 0.38 b	12.68 ± 0.46 ab	10.23 ± 0.28 a	1.38 ± 0.14 a	1.44 ± 0.12 a	1.49 ± 0.16 a	1.42 ± 0.24 a	1.27 ± 0.11 b
	OF2	15.36 ± 0.55 b	14.85 ± 0.38 ab	12.72 ± 0.74 ab	10.12 ± 0.16 a	1.36 ± 0.09 a	1.39 ± 0.11 a	1.51 ± 0.12 a	1.46 ± 0.19 a	1.07 ± 0.08 b
	OF3	16.79 ± 0.58 a	15.45 ± 0.52 a	13.01 ± 0.43 a	10.57 ± 0.26 a	1.30 ± 0.11 a	1.40 ± 0.17 a	1.48 ± 0.15 a	1.38 ± 0.14 a	1.41 ± 0.12 a
	PK	13.54 ± 0.88 c	13.86 ± 1.06 b	12.34 ± 0.27 b	10.17 ± 0.28 a	1.38 ± 0.12 a	1.43 ± 0.06 a	1.51 ± 0.11 a	1.41 ± 0.06 a	−0.57 ± 0.04 c

Note: Data are the means of the three replicates presented as means ± SD. Different letters within the same column indicate significant differences among fertilizer treatments at p < 0.05 (one-way ANOVA).

Table 7

Net GHG balance (NGHGB) and carbon footprint (CF) in maize fields under different treatments.

Year	Treatment	GWPNPP(t CO2-eq.ha−1)	GWPSOC(t CO2-eq.ha−1)	GWPSoil(t CO2-eq.ha−1)	GWPinput(t CO2-eq.ha−1)	NGHGB(t CO2-eq.ha−1)	CF(kgCO2-eq.kg−1)
2021	CK	36.59 ± 2.56 c	−0.74 ± 0.10 c	23.71 ± 1.6 cd	1.25	10.89 ± 2.01 b	0.21 ± 0.02 a
	NPK	50.86 ± 3.12 a	2.33 ± 0.15 b	28.48 ± 0.5 cd	3.65	21.06 ± 2.3 a	0.18 ± 0.01 a
	OF1	52.62 ± 3.96 a	4.23 ± 0.31 b	31.66 ± 3 ab	2.74	23.05 ± 2.08 a	−0.01 ± 0.00 b
	OF2	49.84 ± 2.96 ab	4.16 ± 0.24 b	28.4 ± 1.05 bc	2.77	22.84 ± 2.06 a	−0.02 ± 0.00 b
	OF3	45.2 ± 2.53 b	5.78 ± 0.63 a	34.7 ± 3.94 a	1.32	14.96 ± 1.15 b	−0.25 ± 0.02 c
	PK	36.86 ± 2.68 c	−0.35 ± 0.07 c	22.7 ± 1.01 d	1.74	12.08 ± 1.74 b	0.20 ± 0.01 a
2022	CK	30.87 ± 3.01 c	−1.45 ± 0.12 c	20.91 ± 1.55 b	1.25	7.26 ± 1.51 c	0.28 ± 0.02 a
	NPK	42.13 ± 2.92 a	3.11 ± 0.19 b	25.46 ± 2.21 ab	3.65	16.13 ± 1.79 ab	0.14 ± 0.01 b
	OF1	44.12 ± 3.67 a	3.95 ± 0.24 b	25.33 ± 2.54 ab	2.74	20.00 ± 2.25 a	−0.02 ± 0.00 c
	OF2	41.23 ± 3.21 a	3.93 ± 0.29 b	25.02 ± 2.43 ab	2.77	17.37 ± 1.93 ab	−0.04 ± 0.00 c
	OF3	37.57 ± 2.67 b	5.17 ± 0.47 a	28.27 ± 2.92 a	1.32	13.15 ± 1.78 b	−0.21 ± 0.01 d
	PK	31.51 ± 3.44 c	−2.08 ± 0.12 c	20.97 ± 2.28 b	1.74	6.73 ± 1.23 c	0.38 ± 0.02 a

Note: Data are the means of the three replicates presented as means ± SD. Different letters within the same column indicate significant differences among fertilizer treatments at the p < 0.05 level (one-way ANOVA). A negative CF value indicates that the cropping system is a net carbon sink, where greenhouse gas sequestration exceeds total emissions during the assessment period.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15071703/s1, Figure S1: Monthly temperature and precipitation during the two-year experimental period; Table S1: The emission factor of various agriculture inputs; Figure S2: (a) The correlation between CO₂ fluxes and soil moisture. (b) The correlation between CO₂ fluxes and soil temperature. (c) The correlation between CH₄ fluxes and soil moisture. (d) The correlation between CH₄ fluxes and soil temperature. (e) The correlation between N₂O fluxes and soil moisture. (f) The correlation between N₂O fluxes and soil temperature; Table S2: The impact of different fertilization treatments on soil physicochemical properties; Figure S3: The relationship between CH₄, CO₂, and N₂O emissions and soil physical and chemical properties.

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