DOI: 10.5061/dryad.v6wwpzh1v
title: Data from: Transformation from NHx to NOy deposition aggravated China’s forest soil acidification

description: Elevated nitrogen (N) deposition and changes in reduced or oxidized
 component contribution greatly affect soil acidification. China has
 experienced a significant transformation of N deposition components from
 NHx to NOy over the past 40 years, but the effects of component
 transformation on soil acidification are poorly understood. Therefore,
 long-term monitoring data and literature on N deposition, combined with
 the results of isotope experiments, were used to explore the contributions
 of different N forms on soil acidification in China’s forests. Here, all
 processes related to NHx and NOy, including the transformation to NH4+ and
 NO3-, and subsequent N cycling in the soil, were considered. We found that
 N-induced soil acidification in 80% area of China's forests was
 dominated by NHx deposition, and the other areas (South China) were
 dominated by NOy deposition in 2010s. From 1980 to 2019, the average
 contribution of NHx was higher than that of NOy but the latter
 contribution continued to increase. Meanwhile, the results showed that
 soil acidification increased with the decrease of the ratio of NHx to NOy
 (RNHx/NOy), this is mainly because NOy is more easily leached in the form
 of NO3- than that of NHx under the influence of different plant
 preferences and soil retention rates, resulting in a higher net proton
 production of NOy. Our research has powerful implications for
 policymaking, provides a theoretical basis for formulating different N
 reduction policies in different regions, and points out that the
 synergistic effect of RNHx/NOy changes should be considered to alleviate
 soil acidification.
description: Forests, which account for
 approximately 17% of the total soil area in China, are distributed between
 the latitudes of
 18.46 °N and 52.97 °N and longitudes of 80.82 °E and 133.60 °E. The
 average annual temperature and precipitation in forests in China range
 from 4.3 to 25.1 °C and
 158.9 to 2142.2 mm, respectively. There are five main types of forest:
 evergreen broad-leaf forests, deciduous broad-leaf forests, evergreen
 coniferous forests, deciduous coniferous forests, and coniferous and
 broad-leaf mixed forests.
 Forests in China received 19.80 ~ 41.2 kg N ha<sup>−1</sup>
 yr<sup>−1</sup> N deposition with the highest level in North
 and Central China during the 2010s. Forest soils in China have had a high acidification risk for a long
 time due to serve acid deposition, and N deposition appears to be the primary
 driver.
 2.2
 Quantifying the contribution of NH<sub>x</sub> and
 NO<sub>y</sub> deposition
 The net
 H<sup>+</sup> production of different N forms was used to
 quantify their contribution to soil acidification. Here, we considered all
 the H<sup>+</sup> production and consumption processes induced
 by N deposition including the transformation process of
 NH<sub>x</sub> and NO<sub>y</sub> into
 NH<sub>4</sub><sup>+</sup> and
 NO<sub>3</sub><sup>−</sup> and cycling process of
 NH<sub>4</sub><sup>+</sup> and
 NO<sub>3</sub><sup>−</sup> in soil. First, protons
 are consumed and produced when NH<sub>x</sub> and
 NO<sub>y</sub> are transformed into
 NH<sub>4</sub><sup>+</sup> and
 NO<sub>3</sub><sup>−</sup> via protonation
 and oxidation processes, respectively. The net
 H<sup>+</sup> production through this
 process was calculated
 using Eqs. (1) and (2)
 below: H<sup>+</sup><sub>NHx
 </sub>=
 -NH<sub>4</sub><sup>+</sup><sub>in </sub> (1) H<sup>+</sup><sub>NOy</sub> = NO<sub>3</sub><sup>-</sup><sub>in   </sub> (2) Then NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup> undergo nitrogen cycling in the soil, accompanied by proton production and consumption. The net H<sup>+</sup> production in the soil can also be calculated using Eqs. (3) and (4) [<em>W De Vries and A Breeuwsma</em>, 1987]: H<sup>+</sup><sub>NH4+</sub> = NH<sub>4</sub><sup>+</sup><sub>in</sub> - NH<sub>4</sub><sup>+</sup><sub>L</sub> + NO<sub>3</sub><sup>-</sup><sub>LNH4+ </sub> (3) H<sup>+</sup><sub>NO3-</sub> = NO<sub>3</sub><sup>-</sup><sub>LNO3-</sub> - NO<sub>3</sub><sup>-</sup><sub>in</sub>                  (4) Moreover, the total contribution of NH<sub>x</sub> and NO<sub>y</sub> is calculated using the sums as shown in Eqs. (5) and (6): Con<sub>NHx</sub><sub> </sub>= - NH<sub>4</sub><sup>+</sup><sub>L</sub> + NO<sub>3</sub><sup>-</sup><sub>LNH4+</sub>  (5) Con<sub>NOy</sub>= NO<sub>3</sub><sup>-</sup><sub>LNO3-</sub>                    (6) where H<sup>+</sup><sub>NHx</sub> and H<sup>+</sup><sub>NOy</sub> are the net H<sup>+</sup> production from NH<sub>x</sub> protonated and NO<sub>y</sub> oxidized, respectively. NH<sub>4</sub><sup>+</sup><sub>in</sub> and H<sup>+</sup><sub>NO3-</sub> are the inputs of NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup>. NH<sub>4</sub><sup>+</sup><sub>L</sub><sub> </sub>is the amount of leached NH<sub>4</sub><sup>+</sup>, which is usually so small that it is assumed to be zero. NO<sub>3</sub><sup>-</sup><sub>LNH4+ </sub>and NO<sub>3</sub><sup>-</sup><sub>LNO3-</sub> are the leached NO<sub>3</sub><sup>−</sup> derived from inputs of NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup> (NH<sub>4</sub><sup>+</sup> is converted to NO<sub>3</sub><sup>−</sup> by nitrification and then leached), respectively. 1.3  Isotope experimental methods and data sources To quantify NO<sub>3</sub><sup>−</sup> leaching from NH<sub>x</sub> and NO<sub>y</sub> depositions, integrated isotopic experimental methods were used. Nine paired <sup>15</sup>N-tracer experiments in China’s forests through data integration were conducted . At all sites, only a few (0.1-0.2 kg<sup>15</sup>N ha<sup>−1</sup> in Tieshanping and 0.25 kg<sup>15</sup>N ha<sup>−1 </sup>in the other sites) <sup>15</sup>NH<sub>4</sub><sup>+</sup> or <sup>15</sup>NO<sub>3</sub><sup>−</sup> tracers were systematically added to the forest floors. The recovery of <sup>15</sup>N was measured and calculated at each site to determine the fates of NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup> (including soil, plants, and loss). A regression model was used to scale up the spatial pattern of N loss. More detailed methods and data quality control are available in G A Gurmesa et al. [2022]. N loss consists of leaching and gaseous losses. We established a relationship between leaching losses and gaseous losses for Chinese forest. Finally, combined with the N deposition and isotope parameters, Eqs. (7) and (8) were used to calculate the contribution of NH<sub>x</sub> and NO<sub>y</sub> to soil acidification: Con<sub>NHx</sub> = NH<sub>4</sub><sup>+</sup><sub>in</sub> * N<sub>LossNH4+</sub>*R<sub>leach</sub>  (7) Con<sub>NOy</sub> = NO<sub>3</sub><sup>-</sup><sub>in</sub> * N<sub>LossNO3−</sub>*R<sub>leach </sub>  (8) where N<sub>LossNH4+</sub> and N<sub>LossNO3-</sub> are the loss fractions (<sup>15</sup>N<sub>loss</sub>) for NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup>, respectively. Rleach is the ratio of the leaching loss to the total loss. All units are %. Finally, NH<sub>4</sub><sup>+</sup><sub>in</sub> and NO3-in are the input fluxes of NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup>, respectively, in units of kmolc ha<sup>−1</sup>yr<sup>−1</sup>. 2.4 Atmospheric nitrogen deposition data and analysis The spatiotemporal pattern of N deposition data set (NH<sub>x</sub> and NO<sub>y</sub> depositions) in China from 1980 to 2019 was previously constructed by our group using network monitoring and data integration (Fig. S4). Network monitoring has been conducted in China since 2013 at 54 sites. Data integration collected 2,599 data points on N deposition from 1980 to 2019 (Fig. S5). And Kriging method was used to interpolate and rasterize the data set. More detailed data set on N deposition can be found in our previous studies [<em>G Yu et al.</em>, 2019; <em>J X Zhu et al.</em>, 2015]. Linear regression was used to analyze the relationship between the net H<sup>+</sup> production per unit N deposition and R<sub>NHx/NOy</sub>. All analyses were performed using Origin 2018, SPSS 13.0, and ArcGIS 10.4. Differences were considered statistically significant at P&lt;0.05.