Background & Summary

Food security and air quality are two major issues that currently exist and will persist for a long time, with complex causal relationships that need to be balanced1,2,3. Excessive nitrogen (N) input increased crop yields while resulted in significant losses of reactive N, particularly ammonia (NH3) emissions, which have gradually become a constraining factor affecting the balance4,5,6. Approximately 40% of total NH3 is emitted from N fertilizer application, which has resulted in air pollution, soil acidification, water eutrophication, and biodiversity loss7,8,9,10,11. Therefore, identifying and quantifying the contribution of N fertilizer application to atmospheric NH3 is vital in better understanding the pathways for NH3 emission reduction and determining mitigation options.

The use of 15N natural abundance (δ15N) technology is a complementary tool to identify and quantify the sources of atmospheric NH3 owing to its relatively distinct and well-defined N isotopic signature12,13,14,15,16. Previous studies have found that the δ15N values of NH3 emitted from agricultural sources, such as volatilized fertilizer (−46 ± 5‰) and livestock (−28 ± 11‰), were considerably lower than those emitted from fossil fuel sources (−8 ± 6‰), marine emissions (−10 ± 3‰) and other sources, as reported by Elliott, et al.17 and Bhattarai, et al.18. Therefore, according to the distinct signature of δ15N-NH3 values, the contribution of soil NH3 emissions to atmospheric NH3 can successfully be quantified at present18,19,20. For instance, through the observation of δ15N-NH3 values from major local emissions, the combined contribution of cropland and livestock was found to account for 64.5% of the total NH3 emissions in the Beijing-Tianjin-Hebei region20.

Some studies have investigated δ15N-NH3 values emitted from agricultural sources, but most of them used fixed isotope values to quantify the contribution of cropland volatilization to atmospheric NH3. However, source identification requires knowledge of study area conditions and source emission characteristics. NH3 volatilization is influenced by various factors such as fertilizer application rate, soil NH4+ concentration, and temperature21,22,23,24. These factors directly or indirectly lead to large changes in the δ15N value of NH3 volatilization25,26,27. For instance, temperature is negatively correlated with the δ15N-NH3 value according to field observations19. Moreover, Cejudo and Schiff28 stated that the higher the water pH, the easier the volatilization of 14N, resulting in a lower volatilized δ15N value. Many factors influence the δ15N-NH3 value in the volatilization process of soil NH3, and certain changes can be expected in the temporal or spatial scales. Therefore, the characteristics of δ15N-NH3 values must be studied under different conditions as the use of fixed coefficients may affect the accuracy of traceability results29.

Owing to the complexity of the influencing factors, there is an urgent need to precisely analyze the influence of various factors on δ15N-NH3 values to provide a research basis for subsequent traceability studies. To fill this knowledge gap, we established a comprehensive database on δ15N-NH3 values from soils controlled by seven factors. This database is available from the Figshare repository. The results in this database provided basic data of δ15N-NH3 values for the entire volatilization process in soils and improved the accuracy of the traceability analysis of atmospheric NH3.

Methods

Experiment design

To investigate the δ15N values of soil NH3 volatilization under different conditions, seven controlled laboratory incubation experiments were conducted using the sponge-trapping method. The experiments included fertilization factors (N application rate, and N fertilizer type), meteorological factors (air temperature), soil factors (soil moisture, soil pH, and soil type), and land use type. The detailed experimental design is presented in Table 1.

Table 1 Incubation conditions for the seven experiments (we used sulfuric acid and sodium hydroxide for soil conditioning at different pH levels (pH5, pH6, pH7, and pH8) in Exp5 using soils from Changshu).

Experimental materials

Soil samples were collected from the surface layer of the soil (0–20 cm). Soils of Exp1, 2, and 4 were collected in mid-November 2018 and those of Exp 3 and 5 were collected in mid-November 2019 from Changshu Agro-ecological Experimental Station (31° 32′ 93″ N, 120° 41′ 88″ E), Jiangsu province in eastern China. Soils of Exp6 were collected with the same topography, fertilization, tillage practices, and crop growth conditions, from early September to mid-October 2020 from Beipiao, Liaoning province in northeastern China (41° 57′ N, 120° 36′ E), Xinxiang, Henan province in central China (35° 60′ N, 113° 56′ E), Tangshan, Hebei province in northern China (39° 47′ N, 118° 0′ E), and Linzhi, Tibet in the highlands of southwestern China (29° 34′ N, 94° 25′ E), respectively. Soils of the bamboo forest in Exp7 were collected at Nanjing, Jiangsu province (31° 16′ N, 118° 53′ E), whereas those of vineyard and vegetable growth were collected from Changshu Agro-ecological Experimental Station, Jiangsu province (31° 32′ 93″ N, 120° 41′ 88″ E). Roots and visible rocks in the soil were carefully removed manually, and the soil sample was then air-dried and ground to pass through a 2-mm stainless steel sieve to achieve a high degree of homogeneity. The physicochemical properties of the different sets of soils are listed in Table 2. The δ15N values of urea, compound fertilizer, and ammonium nitrate phosphate fertilizer were −3.6 ± 0.1, −3.0 ± 0.4, and −0.8 ± 0.7‰, respectively.

Table 2 Basic properties of different sets of soil.

Soil physical and chemical analysis

The concentrations of soil NH4+-N and NO3-N were determined using a continuous-flow analyzer (Skalar San++ System, Breda, Netherlands) after filtering, the addition of 5 g of post-culture soil to 50 mL of 2 mol L−1 KCl solution and shaking for 1 h. The minimum detection limits for the NH4+-N and NO3-N concentrations were 0.046 and 0.015 mg N L−1, respectively. Subsequently, soil was removed from the culture bottles to dry in natural air. The soil texture was assessed using the laser diffraction method, soil pH was measured using a glass electrode in a soil: water suspension at 1:2.5(v/v), and soil total nitrogen (TN) content was determined using a Vario Max CN analyzer (Elementar, Vario Max CN, Hanau, Germany) through the dry burning method.

NH3 volatilization measurements

In this study, the sponge-trapping method described by Ti, et al.30 was employed to measure NH3 volatilization under different influencing factors in controlled laboratory incubation experiments. In particular, the NH3 emitted from soil was absorbed in a sponge with an acid solution for staged cultivation. To capture NH3 emissions from the soil, a sponge with a diameter and thickness of 8.5 and 1 cm, respectively, containing 4 mL of glycerol phosphate absorbent was positioned on the neck of a 500-mL incubation bottle. The bottle cap featured a hole with a diameter of 1.4 cm, into which a rubber tube with a diameter of 1.2 cm was inserted. A small sponge with absorbent was placed in this hole to prevent the loss of NH3 from the bottle into the air (Fig. 1).

Fig. 1
figure 1

The schematic diagram of incubation.

The experiment, designed for non-destructive sampling with three replicates, ensured data accuracy. Dry-weight soil was placed in an incubation bottle, and soil moisture was adjusted to a specific percentage of WFPS or SWC by adding deionized water. The specific incubation conditions for the seven sets of experiments are listed in Table 2. Trapping sponges and incubated soils were sampled on days 1, 2, 3, 4, 5, 6, 7, and 15 (excluding day 7 for experiment Exp6). At each sampling interval, the removed trapping sponges were plunged into 50 mL of 1 mol L−1 KCl, shaken for 2.5 h at 100 rotations per minute for NH4+-N sample extraction, and analyzed for NH4+-N using a continuous-flow analyzer.

N isotopic analysis

The δ15N-NH3 values were measured using the method described by Liu, et al.31. This method relies on the isotopic analysis of nitrous oxide (N2O). By examining the linear correlation between the δ15N values of the substrate (NH4+) and resulting gas (N2O), a standard curve was fitted, enabling the deduction of the δ15N-NH4+ values of the substrate. The isotope ratio is reported in parts per thousand relative to atmospheric N2 according to Eq. (1).

$${\delta }^{15}{{\rm{N}} \mbox{-} {\rm{NH}}}_{{\rm{x}}}(\textperthousand )=\frac{{({\rm{N}}15/{\rm{N}}14)}_{{\rm{sample}}-}{({\rm{N}}15/{\rm{N}}14)}_{{\rm{standard}}}}{{({\rm{N}}15/{\rm{N}}14)}_{{\rm{standard}}}}\times 1000$$
(1)

The N isotopic compositions of all the samples were analyzed using an isotope mass spectrometer (Isoprime 100, Isoprime, UK). International reference δ15N-NH4+ standards, namely, USGS25 (−30.4‰), USGS26 (+53.7‰), and IAEAN1 (+0.4‰), were chosen for data correction purposes.

Data Records

The dataset is available at Figshare32, an open-access repository where users can make all their research outputs available in a citable, shareable, and discoverable manner. The Excel file was named Natural Isotopic Abundance of Soil Ammonia Volatilization Excel Data.xlsx. This file provided complete information on the seven controlled experiments, including experiment sets (array named Set), days of incubation (array named Day), experimental treatment (array named Treatment), the mean values of δ15N-NH3, cumulative NH3, soil NH4+-N, soil NO3-N, soil pH, and their standard deviations (array named sd). The data for Exp1, Exp2, Exp6, and Exp7 have been published and were described in detail29,30,33,34.

Technical Validation

The data were collected and measured using a standardized protocol and calibrated continuous-flow analyzer and an isotope mass spectrometer. Each experiment was repeated thrice to ensure the accuracy of the results. The data were analyzed using appropriate statistical methods to identify the significant effects of the different factors on δ15N-NH3 values emitted from soils.

Usage Notes

This dataset provides a valuable resource for researchers and policymakers, as well as those who are interested in agricultural sources of atmospheric NH3 and effective strategies to reduce NH3 emissions and protect the environment. This dataset can also be used to validate the “bottom-up” emission inventory methodology and model simulations.