The Impact of Biochar Application on Soil Mineral Nitrogen and Greenhouse Gas Fluxes (N₂O and NH₃) in Luvic Anthrosols

Biochar application in agriculture has gained increasing attention due to its potential to positively impact crop productivity and climate change mitigation. Biochar can directly and indirectly influence carbon (C) and nitrogen (N) processes in soil. This study investigated the impact of biochar use on agricultural soils in the Russian Far East focusing on the greenhouse gas fluxes of nitrogen oxide (N2O), reactive ammonia (NH3), and mineral forms of soil nitrogen. The feasibility of gas flow rate data with low R2 values measured by a highly sensitive gas analyzer was assessed. The experimental field plots were part of the Primorskaya Vegetable Experimental Station of the All-Russian Scientific Research Institute of Vegetables, located near Surazhevka village in the Primorsky District of the Russian Far East (43°25'22.4"N 132°18'50.6"E). The study was conducted in spring and summer of 2019, between 11 and 16 months after biochar had been applied to the soil. Three plots were treated with biochar at doses of 0 kg/m2 (BC0kg), 1 kg/m2 (BC1kg), and 3 kg/m2 (BC3kg) (See Fig. 2). The biochar were applied to the topsoil (0-10 cm) on June 15, 2018. No mineral or organic fertilizers were added to the experimental plots. Biochar was produced from birch (Betula alba) by slow pyrolysis at temperatures ranging from 360°C to 380°C. The biochar contained 78% carbon (C), the H/C and O/C ratios were 0.0518 and 0.1452, respectively, and pH 8.09 (See Table 1). In 2019, soybeans were grown in the experimental plots. Soybeans were sown on June 28, 2019 and harvested for yield and dry biomass assessment from October 10 to October 12, 2019. Afterwards, soybean biomass was used by the farmer as green fertilizer to enrich the soil with nitrogen. The soil in the experimental areas is classified as Luvic Anthrosols and has silt loam texture according to the FAO classification. N2O and NH3 fluxes and concentrations of N-NH4+ and N-NO3 were monitored from May to October 2019. The area of each plot was 21.6 m2. The plots were divided into three subplots. Three intact soil cores (three aluminum cores with a volume of 78.5 cm3) were collected from each subplot, resulting in 27 soil cores selected for each measurement (135 soil cores for the measuring period). When soil cores were taken to determine N2O and NH3, field soil moisture was measured with a Delta-T SM150 sensor (Devices Ltd, England) and soil temperature was measured at a depth of 10 cm. Four additional soil cores were collected from each subplot to estimate mineral nitrogen concentrations and to determine N2O and NH3. The N2O and NH3 fluxes from the intact cores were measured in the laboratory using a Picarro G2508 laser gas analyzer (Picarro Inc., Santa Clara, CA, USA). Three soil cores were placed in a 1-liter glass chamber equipped with a gas lid and inlet and outlet ports with a gasket ring connecting the internal volume of the glass chamber to a gas analyzer with Teflon tubes. The integration time for Picarro analysis was 5 minutes. Temperature and air pressure in the laboratory were also measured using a Vaisala WXT520 weather sensor (Vaisala, Helsinki, Finland). Concentrations of N-NH4+ and N-NO3" in the soil were determined by the colourimetric method using a UV-1280 single-beam spectrophotometer (Shimadzu, Japan). The study revealed no effect of biochar on soil moisture and temperature in the field (See Fig. 2, 3). When comparing soil moisture with biochar application rates, a statistically significant effect (P = 0.001) of soil moisture reduction was observed in the BC1kg treatment compared to the BC0kg plot. Although a similar trend was observed for the BC3kg treatment (P = 0.03), the latter was not significantly different from the plots BC0kg and BC1kg. Soil temperatures during the experiment did not vary significantly between treatments (P = 0.99). Soil temperature correlated with air temperature throughout the experimental period (P = 8.6x10-6). No correlation was found between biochar application rates and values of N-NH4+ (P = 0.98) and N-NO3- (P = 0.88). The N-NH4+ and N-NO3- values correlated with the month of measuring (P = 0.007). The results of N2O flux measurements showed no statistical relationship with the biochar application rates (P = 0.87) (See Fig. 5). When calculating N2O fluxes, it was found that all fluxes have very low R2 values (from 5.7x10-7 to 0.38). It is generally assumed that the data with similar R2 values are statistically insignificant, but this is not entirely correct. N2O formation is a very complex process, and a large number of factors contribute to its high variability and, thus, high fluctuation of indicators. The complex nature of the N2O production makes it sensitive to real-time measurements, especially in disturbed soils. In some soils, emissions of N2O or other gases may be low and unstable. In this case, high-precision real-time measurement techniques may result in a concentration profile with high fluctuations. Conventionally, a linear regression equation is used to estimate N2O fluxes. However, high fluctuations lead to frequent deviations of values from the trend line, resulting in low R2 values. This study employed an optical method to measure gases using a Picarro G2508 laser gas analyzer based on the cavity ring-down spectroscopy (CRDS) system. This gas analyzer is designed to measure at a rate of 53 readings per minute and offers high sensitivity in measuring gas concentrations (ppb). The measurements yielded data with high variations in N2O concentration (See Fig. 6). High fluctuations in N2O concentration resulted in low R2 values when using a linear flux regression. The Picarro G2508 can simultaneously measure CO2, CH4, N2O, NH3, and H2O. If measured correctly, CO2 always exhibits a good linear relationship. The previous research showed that CO2 fluxes had statistically significant R2 values greater than 0.9. Since N2O and CO2 were measured simultaneously, the high R2 index for CO2 implies that the N2O measurement is correct. The results for NH3 fluxes were quite variable (See Fig. 7). The lowest flux values were recorded in the warmer months (June and July) when crops were increasing. In May and October, the NH3 emissions were similar. The BC0kg and BC1kg plots showed almost identical results, but the flux was higher in the BC3kg plot. Thus, in May, the flux at the BC3kg plot was 40% higher than that at the BC0kg plot. In October, there was a 69% increase in flux at the BC3kg plot compared to BC0kg. May and October are not sufficiently conducive to microbiological activity, as shown in Figure 4. However, the similarity in the distribution of NH3 fluxes suggests that biochar can significantly change the temperature around the particles on the soil surface, i.e., it can create warm zones favourable for living microorganisms. This might be explained by the black colour of biochar (high in carbon), which absorbs solar radiation. Therefore, higher NH3 rates at the BC3kg plot may be related to greater microbial activity around the warm zones near biochar particles. The article contains 7 Figures, 2 Tables and 40 References. The authors thank the staff of the Primorsky Vegetable Experimental Station - a branch of the Federal State Scientific Institution "Federal Scientific Center of Vegetable Growing" (a branch of the FSSI FSCVG) for providing experimental plots and assistance in conducting research. We express special gratitude to Tarasova Tatiana Sergeevna, Researcher of the branch of the FSSI FSCVG and Sakara Nikolai Andreevich, PhD, Director of Science of the branch of the FSSI FSCVG.

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