Monthly Variations of the Nitrogen Isotope of Ammonium in Wet Deposition in a Tropical City of South China

Received: June 13, 2019
Revised: March 5, 2020
Accepted: March 19, 2020
Download Citation: RIS|BibTeX|https://doi.org/10.4209/aaqr.2019.06.0303  

Cite this article:

Chen, F., Lao, Q., Li, Z., Bian, P., Zhu, Q., Chen, C. and Song, Z. (2020). Monthly Variations of Nitrogen Isotope of Ammonium in Wet Deposition in a Tropical City, South China. Aerosol Air Qual. Res. 20:1062-1069. https://doi.org/10.4209/aaqr.2019.06.0303

HIGHLIGHTS

• Sunshine duration was the most important factor controlling isotopic changes.
• The SO₂ and NO_x oxidation resulted in 15N-enriched residual NH₄⁺ in wet seasons.
• NH₄⁺ in precipitation in Zhanjiang mainly derived from combustion sources (63%).

Keywords: Ammonium; δ15 33 N; wet deposition; Bayesian isotope mixing model; tropical area

INTRODUCTION

Nitrogen (N) is an important element in the ecosystem (Galloway et al., 2008; Xiao et al., 2012). Recently, excessive anthropogenic N emissions have greatly increased N deposition, particularly from the 1980s through the early 21^st century (Galloway et al., 2004; Fang et al., 2010; Xu et al., 2017; Biswas et al., 2019). Increasing N deposition has induced harmful effects on the ecosystem and atmospheric environment (Galloway et al., 2004; Fang et al., 2010; Jiang et al., 2019). Ammonium (NH₄⁺) is an important form of N deposition (Galloway et al., 2008; Liu et al., 2013) and mainly originates from fossil fuel consumption, volatilized sources (e.g., animal wastes and fertilizer) and biomass burning (Huang et al., 2012; Kang et al., 2016; Zheng et al., 2018; Peng et al., 2019). Previous studies indicate that the increase in ammonia (NH₃) emissions from 1980s to first few years of the 21^st century in China was mostly from livestock waste (49%) and synthetic fertilizer applications (37%), and remain stable or slightly decreased over the past few years (Kang et al., 2016). However, the ammonia concentration in atmosphere is still high, and has caused serious environmental pollution (Xiao et al., 2012; Liu et al., 2013; Liu et al., 2017; Zheng et al., 2018).

Nitrogen isotope in ammonium (δ¹⁵N-NH₄⁺) in precipitation provide a valuable geochemical tracing technique called fingerprint identification (Xie et al., 2008; Jia and Chen, 2010; Xiao et al., 2012; Altieri et al., 2015; Liu et al., 2017), which is powerful to trace the sources of NH₄⁺ and the reaction process of deposited NH₄⁺ in ecosystems (Jia and Chen, 2010; Altieri et al., 2016; Liu et al., 2017). For example, δ¹⁵N in wet deposition has been used successfully to identify NH₄⁺ sources in Guangzhou (Jia and Chen, 2010); Guiyang (Xiao et al., 2012; Liu et al., 2017; Zheng et al., 2018); the Yangtze River Delta region (Zhao et al., 2009); Chengdu (Li et al., 2007); Pretoria, South Africa (Heaton, 1987); and Niigata Platin, Japan (Fukuzaki and Hayasaka, 2009). In addition, based on the stable isotope mixing model, Liu et al. (2017) found that volatilization sources (animal waste [22%] and fertilizer [22%]) contributed less pollution than ammonia derived from combustion sources (vehicle exhaust [19%], coal combustions [19%] and biomass burning [17%]) in Guiyang, China. Moreover, δ¹⁵N-NH₄⁺ in wet deposition can be modified by weather conditions (Jia and Chen, 2010; Xiao et al., 2012). For example, washout processes preferentially incorporate heavy isotopes (¹⁵N), which leads to heavier δ¹⁵N-NH₄⁺ in precipitation (Xiao et al., 2012). Sunshine duration also influences δ¹⁵N-NH₄⁺ in precipitation because free radicals and photooxidation can produce sulfur dioxide (SO₂) and nitrogen oxide (NO_x) to acidic matter (H₂SO₄ and HNO₃) in the atmosphere, which accelerates the transition of NH₃ (gas phase) into (NH₄)₂SO₄ and NH₄NO₃ (particulate phase) by unidirectional reactions for isotopically enriched ¹⁴N (Xiao et al., 2012). This process results in ¹⁵N-enriched residual NH₃ (NH₄⁺) in wet deposition. However, these studies mainly focus on the middle and high latitudes. In contrast, little is known about ammonium sources and the composition of nitrogen isotopes in precipitation in low latitude areas, which exhibit significantly different weather conditions relative to the middle and high latitude areas.

In this study, a time series investigation of NH₄⁺ concentrations and δ¹⁵N-NH₄⁺ in wet deposition was conducted from October 2015 to November 2018 in Zhanjiang, a typical tropical area in the southernmost region of mainland China. We strived to identify the main factors that control seasonal variations of δ¹⁵N-NH₄⁺ and to elucidate the different sources of NH₄⁺ in wet deposition in such tropical areas.

MATERIALS AND METHODS

Sampling Station and Sample Collection

Rainwater samples were collected in Zhanjiang (20.00–21.58°N, 109.52–110.92°E), which is located in western Guangdong Province in South China near the northern extent of the South China Sea (Fig. 1). As a tropical city, Zhanjiang has a tropical monsoon climate with relatively high annual mean temperatures (23.0°C) and high annual mean rainfall (1689 mm; China Meteorological Data Service Center, http://data.cma.cn/). The annual duration of sunshine in Zhanjiang is very long (~2000 hours) due to its low latitude (China Meteorological Data Service Center, http://data.cma.cn/n). The transitional months from the winter monsoon to the summer monsoon usually occur in spring, with rainfall sharply increasing in May, and subsequently decreasing after October (Fig. 2(e)). Thus, the wet season is defined as taking place from May to October, and the dry season is defined as taking place from November to April. 

Fig. 1. The sampling site in Zhanjiang, South China (black dot). WM: winter monsoon; SM: summer monsoon.

Fig. 2. Comparisons of δ¹⁵N-NH₄⁺ with NH₄⁺ concentration and atmospheric parameters in Zhanjiang. Monthly (a) sunshine duration, (b) temperature, (c) SO₂ and NO₂ concentration, (d) δ¹⁵N-NH₄⁺ and (e) rainfall and NH₄⁺ concentration. The lack of NH₄⁺ concentrations and δ¹⁵N-NH₄⁺ in Feb 16, Dec 16, Jan 17 and Dec 17 is because very little (< 0.5 mm) or no rainfall occurred during these periods.

From October 2015 to November 2018, rainwater samples were collected for each precipitation event on the roof of a building at Guangdong Ocean University in Zhanjiang. A dry polyethylene bucket (80 cm in diameter) cleaned with acid was used to collect rainwater. Rain events with rainfall less than 0.5 mm were considered invalid and not collected. After collection, the rainwater samples were filtered through glass fiber filters (GF/Fs; 47 mm in diameter; Whatman) and into polyethylene bottles, which were previously soaked with 30% (v/v) HCl for 24 h and cleaned with ultrapure water and dried in the laboratory. Samples were stored frozen at –20°C, and they were analyzed soon after being melted. Similar procedures have been conducted in numerous studies (e.g., Jia and Chen, 2010; Liu et al., 2017; Xiao et al., 2012; Zheng et al., 2018). During the period from October 2015 to November 2018, 315 rainwater samples were collected. The rainwater samples collected each month were proportionally mixed into a large sample according to the rainfall amount that month, thus composing a representative sample of wet deposition for the entire month. The results of the analysis of NH₄⁺ concentrations in the mixed samples are monthly weighted averages.

Sample Analysis

NH₄⁺ concentrations were determined by spectrophotometry after treatment with Nessler’s reagent, and the detection limit was lower than 0.1 mg L^–1. For the isotopic analysis, NH₄⁺ was first quantitatively oxidized to NO₂^– by hypobromite (BrO^–) at a pH of 12. Excess BrO^– was consumed by sodium arsenite. NO₂^– was further reduced to N₂O with 1:1 sodium azide in an acetic acid buffer (Lin et al., 2007). Subsequently, N₂O was separated, purified and analyzed for δ¹⁵N with a GasBench II-MAT 253. The international standards, IAEA-N1, USGS 25 and USGS 26, were used for δ¹⁵N calibration. The analysis deviation for the standard was < 0.2‰ for δ¹⁵N. The reproducibility of duplicate analyses was < 0.3‰ for δ¹⁵N (average ± 0.1‰).

Data Sources and Calculations

Monthly atmospheric SO₂ data was from historical air quality data in Zhanjiang (China air quality online monitoring and analysis platform, https://www.aqistudy.cn/). The sunshine duration, temperature, humidity, wind direction and wind speed were obtained from the China Meteorological Data Sharing Service System (China Meteorological Data Service Center, http://data.cma.cn/).

Backward Trajectories

To reveal possible sources of pollutants, the web version of the model Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was used to calculate three days (72 h) of back trajectories (BTs; https://ready.arl.noaa.gov/HYSPLIT_traj.php). The BTs were generated from the sampling location at a height of 500 m above sea level. A trajectory time of three days (72 h) was chosen due to the short residence time of NH₄⁺ in the atmosphere (less than three days) (Xiao and Liu, 2002).

Stable Isotope Analysis in R (SIAR) Mixing Model

To calculate the proportional contribution of potential NH₄⁺ sources in Zhanjiang, a Bayesian stable isotope mixing model was conducted using the SIAR package. In this model, a Bayesian framework was used to calculate the probability distribution for the proportion of each source to the mixture. The following equation was used:

where X_ij denotes the isotopic values (j = 1, δ¹⁵N-NH₄⁺) of the sample i (i = 1, 2, 3, …, N); S_jk denotes the isotopic value j of the source k (k = 1, 2, 3, …, K), which is normally distributed with the average μ_jk and the standard deviation ω_jk; P_k denotes the contribution of source k, which is determined by the SIAR model; c_jk denotes the fractionation factor for j in source k, where c_jk is normally distributed with the average λ_jk and the standard deviation τ_jk; and ε_jk denotes the residual error of the additional unquantified variation between individual samples, which are normally distributed with average 0 and standard deviation σ_j. This model was used by previous studies, therefore a more detailed model description can be found in Moore and Semmens (2010), Xue et al. (2012) and Zhang et al. (2018).

RESULTS

Monthly rainfall, NH₄⁺ concentration, δ¹⁵N-NH₄⁺ values, SO₂ and NO₂ concentration, sunshine duration and temperature, recorded from October 2015 to November 2018, are summarized in Fig. 2. The lack of NH₄⁺ concentrations and δ¹⁵N-NH₄⁺ during February 16, December 16, January 17 and December 17 is because very little (< 0.5 mm) or no rainfall occurred during these periods. The average NH₄⁺ concentration ranged from 0.43 to 3.11 mg L^–1 during the sampling period, with an average of 0.82 mg L^–1. Considering only the annual averages, we find that there is no significant trend in the variation of NH₄⁺ concentration. The annual mean NH₄⁺ concentration are 1.04 mg L^–1, 0.65 mg L^–1 and 0.78 mg L^–1 in 2016, 2017 and 2018, respectively, suggesting that the concentrations of NH₄⁺ slightly decreased after 2016. Compared with the wet seasons, higher concentrations of NH₄⁺ were found during the dry seasons (Fig. 2(e)). According to the precipitation and annual mean NH₄⁺ concentration during the three study years, wet NH₄⁺-N deposition in 2016, 2017 and 2018 in Zhanjiang was 22.7 kg N ha^–2, 13.3 kg N ha^–2 and 19.0 kg N ha^–2, respectively. The δ¹⁵N-NH₄⁺ ranged from –18.0 to –3.9‰, with an average of –9.6‰. The δ¹⁵N-NH₄⁺ showed higher values during the wet seasons relative to lower values during the dry seasons, which is consistent with variations in rainfall, sunshine duration and temperature, but contradictory to variations in SO₂ and NH₄⁺ concentrations (Fig. 2). This pattern in variation of δ¹⁵N-NH₄⁺ in Zhanjiang is different from other areas, such as Guizhou in western China (Xiao et al., 2012), which exhibited higher values in winter and lower values in summer.

DISCUSSION

Concentration of NH₄⁺ in Precipitation

In this study, the NH₄⁺ concentration in rainwater in Zhanjiang is lower than in Guangzhou (1.10 mg L^–1; Jia and Chen, 2010), Guiyang (1.98 mg L^–1; Xiao et al., 2012) and in the Yangtze River Delta region (1.20 mg L^–1; Zhao et al., 2009), but higher than the subtropical forest ecosystems in remote areas of South China (ranged from 0.02 to 0.05 mg L^–1; Chen and Mulder, 2007). The wet deposition fluxes in Zhanjiang (18.3 kg N ha^–2 in three year average) are slightly lower than that reported values observed in Guangzhou (27.4 kg N ha^–2; Jia and Chen, 2010) and Guiyang (23.2 kg N ha^–2; Xiao et al., 2012), and higher than that in the Yangtze River Delta region (14.9 kg N ha^–2; Zhao et al., 2009), indicating significant N pollution in the city. In areas with intensive human activities, anthropogenic sources (such as industrial activities and agricultural productivity) may provide the most important contribution to NH₄⁺ in wet deposition. In addition, sources of NH₄⁺ include natural sources, such as human and animal excrement and fertilizer, which are closely associated with agricultural activities (Jia and Chen, 2010; Peng et al., 2019; Zhao et al., 2009). The annual averages of NH₄⁺ concentration are 1.04 mg L^–1, 0.65 mg L^–1 and 0.78 mg L^–1 in 2016, 2017 and 2018, respectively, suggesting that the NH₄⁺ pollution is in an unstable level. This interannual variation might be related with the weather parameters, which will be monitored in the future to clarify this issue. Due to the seasonal distribution pattern, higher NH₄⁺ concentrations occur in the dry seasons (November–April) and lower concentrations occur in the wet seasons (May–October); this pattern may be attributed to the dilution of rainfall (Fig. 2(e)) and/or the origin of air masses (Fig. 3). The dominant air mass over the continent of China in the dry season could bring highly polluted continental air to Zhanjiang, whereas the dominant air mass from the southerly ocean could bring clean air to the city (Fig. 3). In addition, temporal changes in the relative contributions of different sources could affect nitrogen isotopes, as discussed later.

 Fig. 3. Backward air mass trajectories in precipitation events in Zhanjiang, based on NOAA HYSPLIT model back trajectories; the red lines denote air mass trajectories occurring in the wet season and the blue lines denote trajectories in the cool dry seasons. (For interpretation of the references to the color in this figure, the reader is referred to the Web version of this article.)

Influencing Factors of δ¹⁵N-NH₄⁺ in Precipitation

The δ¹⁵N-NH₄⁺ in Zhanjiang was similar to those reported in Guiyang (Xiao et al., 2012) and Guangzhou (Jia and Chen, 2010), but the seasonal distribution pattern is the opposite, exhibiting higher values in the wet seasons and lower values in the dry seasons. This seasonal distribution pattern may be controlled by washout, temperature and sunshine duration (Xiao et al., 2012). If rainfall was the key factor influencing the seasonal patterns, low precipitation during the dry seasons would preferentially wash out heavy ¹⁵N-NH₃, then higher δ¹⁵N-NH₄⁺ occurred in wet deposition. In contrast, complete NH₃ removal would result in relatively lower δ¹⁵N-NH₄⁺ in wet deposition during the wet season than the dry one. In fact, a positive correlation between δ¹⁵N-NH₄⁺ and rainfall was observed in Zhanjiang, and generally high δ¹⁵N-NH₄⁺ were found during the rainy seasons (Fig. 2). This suggests that the isotopic effect of washout may be less important for δ¹⁵N-NH₄⁺ in Zhanjiang. Significantly high temperatures were observed during the wet seasons in Zhanjiang. With increasing temperatures, microbial activity will increase and facilitate more ¹⁴N-organic matter in the atmosphere to decompose into NH₄⁺, resulting in negative values of δ¹⁵N-NH₄⁺ (Xie et al., 2008; Xiao et al., 2012). In addition, temperature can increase the volatility of NH₃ from sources, leading to lighter NH₃ molecules being released into the atmosphere (Sommer et al., 1991; Xiao et al., 2012). However, higher δ¹⁵N-NH₄⁺ were found during the wet seasons (higher temperature) in Zhanjiang (Fig. 2). This suggests that temperature was not an important factor controlling seasonal variations of δ¹⁵N-NH₄⁺ in Zhanjiang. Therefore, sunshine duration is the most likely factor controlling the variations of δ¹⁵N-NH₄⁺ in precipitation discussed below.

NH₃ in the atmosphere is easily absorbed by acidic matter (e.g., H₂SO₄ and HNO₃; Xiao et al., 2012). A significantly longer sunshine duration provided more photooxidation opportunities and free radicals that produce more sulfur dioxide (SO₂) and nitrogen oxide (NO_x) to acidic matter (H₂SO₄ and HNO₃), thereby accelerating the unidirectional conversion of light ¹⁴N-NH₃ to (NH₄)₂SO₄ and NH₄NO₃ (Freyer, 2010; Ottley and Harrison, 1992; Pavuluri et al., 2010). In addition, rain flushing is another way to consume SO₂ and NO_x. Thus, these reaction processes and heavy rainfall resulted in lower SO₂ and NO_x concentrations during the wet seasons. However, rain flushing only occurred in precipitation event, while the reaction processes that produced SO₂ and NO_x to acidic matter (H₂SO₄ and HNO₃) occurred at all time. Thus, the reaction process may be the most important way to consume SO₂ and NO_x. These products by reaction processes are solids, which can be adsorbed and deposited by aerosols. This process results in ¹⁵N-enriched residual NH₃ in atmosphere. When it rains, rain mainly capture ¹⁵N-enriched residual NH₃ to produce NH₄⁺ (Xiao et al., 2012). We realize that rain can also capture NH₄⁺ from (NH₄)₂SO₄ and NH₄NO₃ in aerosol. However, (NH₄)₂SO₄ and NH₄NO₃ in aerosol were deposited all the time, thus NH₄⁺ in rain sourced from aerosol seems to be less important (Xiao et al., 2012). In addition to the sunshine (photooxidation and free radicals) pathway for the formation of acidic matter, SO₂ can be also oxidized by natural transition metal ions to form H₂SO₄ (Harris et al., 2013). However, this oxidation pathway by metal ions primarily occur on coarse mineral dust, and the sulfate produced has a short lifetime and little direct or indirect climatic effect (Harris et al., 2013). Thus, this oxidation pathway by metal ions can be less important for the formation of acidic matter. As shown in Fig. 2, there is a significant correlation between sunshine hours and δ¹⁵N-NH₄⁺ in Zhanjiang, indicating that sunshine duration was indeed the most important factor affecting seasonal variations of δ¹⁵N-NH₄⁺. SO₄^2– and NO₃^– are the most abundant chemical component anion in precipitation (Xiao et al., 2012) and total suspended particulate (TSP; Xiao and Liu, 2004). Thus, the predominant SO₂ and NO_x oxidation pathways may be considered as a driver for the trends of δ¹⁵N-NH₄⁺. The photooxidation and reaction with free radicals are the main oxidation pathways of SO₂ and NO_x in the atmosphere. The rate of photooxidation is about 1% SO₂ h^–1, thus the longer sunshine time would produce more oxidation products. In addition, since the formation of free radicals need sunshine, the high free radicals generally occur in summer and low free radicals occur in winter (Xiao et al., 2012). Due to its low latitude, the sunshine duration of Zhanjiang is relatively longer in the wet season and shorter in the dry season (Fig. 2(a)). In Zhanjiang, due to longer sunshine time in this tropical area, NO_x oxidation via free radical was the predominant pathway (accounting for 87% in winter and 94% in summer; Chen et al., 2019). Further SO₂ and NO_x oxidized by photooxidation and free radicals in the atmosphere produces more H₂SO₄ and HNO₃ (Fig. 2(c)). The more H₂SO₄ and HNO₃ is produced, the more ammonia is absorbed onto (NH₄)₂SO₄ and NH₄NO₃, which can be deposited by aerosols. The reaction of ammonia with H₂SO₄ and HNO₃ is a kinetic process (unidirectional reactions) that favors the light isotope of nitrogen in the product, and leads to ¹⁵N-enriched residual NH₄⁺ in wet deposition (Xiao et al., 2012). Thus, the significantly longer sunshine duration in the wet season and shorter sunshine duration in the dry season may be responsible for the seasonal variations of δ¹⁵N-NH₄⁺ in Zhanjiang. The pattern of seasonal variation of δ¹⁵N-NH₄⁺ in Zhanjiang is opposite to the patterns in Guiyang (Xiao et al., 2012) and Guangzhou (Jia and Chen, 2010), where higher δ¹⁵N-NH₄⁺ occurred in winter and lower values occurred in summer. In contrast to this study, the authors considered temperature to be the most important factor controlling seasonal variations of δ¹⁵N-NH₄⁺ in Guiyang (Xiao et al., 2012) and Guangzhou (Jia and Chen, 2010). This is likely due to shorter sunshine durations in those areas, particularly in Guiyang, which averages only 78 h month^–1 (ranging from 42 to 159 h month^–1) of sunshine (Xiao et al., 2012). In contrast, the amount of sunshine in Zhanjiang is significantly greater (average of 150 h month^–1 in 2016 and 154 h month^–1 in 2017). Therefore, we hypothesize that sunshine duration is the most important factor controlling seasonal variations of δ¹⁵N-NH₄⁺ in precipitation in Zhanjiang, a typical tropical area.

Sources of NH₄⁺ in Precipitation

The δ¹⁵N of dominant NH₃ emissions are distinct and well characterized as shown in Table 1. The δ¹⁵N in fertilizer and animal waste is relatively low, while δ¹⁵N from biomass burning and fossil fuel-derived NH₃ are higher (Table 1). As discussed above, isotopic fractionation occurred significantly in the wet seasons due to a longer sunshine duration, suggesting that the δ¹⁵N-NH₄⁺ values in wet seasons were not suitable to be used in the model to quantify the proportional contribution of the sources. On contrast, isotopic fractionation would be less in the dry seasons due to a shorter sunshine duration. Thus, it is more representative to apply δ¹⁵N-NH₄⁺ from the dry seasons to identify ammonia sources in Zhanjiang. Here, relative contributions of the sources listed above were estimated in wet deposition using a Bayesian model. Outputs from the SIAR mixing model show that precipitated NH₄⁺ in Zhanjiang originated more from fossil fuel-derived ammonia emissions (24 ± 26% from vehicle exhaust, 28 ± 26% from coal combustion) than from volatilized ammonia emissions (18 ± 21% from animal waste, 19 ± 20% from fertilizers) and biomass burning (11 ± 5%) (Fig. 4). Summarily, the result of our estimation showed that fossil fuel-derived ammonia emissions dominated Zhanjiang (52%), which was similar to estimates in Guiyang (38%; Liu et al., 2017). In Guiyang, the depletion of δ¹⁵N-NH₄⁺ in precipitation for the past decades was attributed to ammonia emissions from domestic waste and sewage (Xiao and Liu, 2002). However, the latest research showed that the ammonia in precipitation in Guiyang was originated from fossil fuel-derived ammonia emission and biomass burning than from domestic waste and sewage and fertilizer (Liu et al., 2017). This is mainly influenced by the increasing human activities. In Zhanjiang, coal is commonly used to generate electricity (Chen et al., 2019). In addition, the dominant air mass over the continent of China during the dry seasons could bring highly polluted continental air to Zhanjiang (Fig. 3). Combustion ammonia sources particularly that from fossil fuels substantially contributed to the observed δ¹⁵N-NH₄⁺ in precipitation in this tropical city, which should be emphasized in source of anthropogenic ammonia deposition. This suggestion agrees with the bottom-up inventory, which reveals that most N emissions are derived from coal combustion in China (Fang et al., 2010). Therefore, our results indicate that δ¹⁵N-NH₄⁺ in precipitation is more applicable for source identification in dry seasons than in wet seasons in Zhanjiang due to minimal isotope fractionation. 

Fig. 4. Percentage contribution of five potential NH₄⁺ sources (VE: vehicle emissions; CC: coal combustion; BB: biomass burning; AW: animal waste; F: fertilizer) for dry season deposition estimates by SIAR.

CONCLUSIONS

The NH₄⁺ and δ¹⁵N-NH₄⁺ in the wet deposition in Zhanjiang averaged 0.82 mg L^–1 and –9.6‰, respectively. The NH₄⁺ exhibited higher concentrations during the dry season than the wet one. Comparing the δ¹⁵N-NH₄⁺ with seasonal patterns of different weather parameters, we found the observed temporal isotopic variation to be primarily caused by the change in sunshine duration. During the wet season, a significantly longer duration increased the opportunities for photooxidation and enhanced the formation of free radicals that produced H₂SO₄. This process accelerated the unidirectional conversion of NH₃ into (NH₄)₂SO₄- and NH₄NO₃-enriched ¹⁴N particles, which can be deposited by aerosols, and resulted in lower atmospheric concentrations of SO₂ and NO₂ and higher levels of ¹⁵N-enriched residual NH₄⁺. By contrast, less isotopic fractionation occurred during the shorter sunshine duration of the dry season, suggesting that δ¹⁵N-NH₄⁺ in the precipitation should be similar to those of NH₃ in the atmosphere and can be applied in source apportionment. A Bayesian model demonstrated that a higher proportion of the concentration of NH₄⁺ in Zhanjiang’s precipitation was contributed by fossil fuel-derived sources (including vehicle exhaust and coal combustion) than ammonia volatilization and biomass burning.

ACKNOWLEDGEMENTS

This work was supported by the National Key Research and Development Plan (2016YFC1401403), the National Natural Science Foundation of China (41476066, 41466010, and 41676008), the Guangdong Natural Science Foundation of China (2016A030312004), the International Science and Technology Cooperation Project (GASI-IPOVAI-04), the Fund of Key Laboratory of Global Change and Marine Atmospheric Chemistry (GCMAC1609), and the Project of Enhancing School with Innovation of Guangdong Ocean University (GDOU2016050260).