Developing Nitrogen Isotopic Source Profiles of Atmospheric Ammonia for Source Apportionment of Ammonia in Urban Beijing

Atmospheric ammonia (NH₃) is the key precursor in secondary particle formation, which is identified as the most abundant components of haze in Beijing in most cases. It is critical to understand the characteristics of NH₃ from various emission sources and quantify each source contribution to NH₃ in ambient atmosphere. Stable nitrogen (N) isotope composition (δ¹⁵N) is an effective tool to study NH₃ source. However, this tool cannot be effectively applied in Beijing due to the lack of comprehensive N nitrogen isotope source profiles. Reliable source profiles are the basis of source apportionment of NH₃ using the isotope mixing model. In this study, multiple NH₃ source samples were collected at sites, representing six major NH₃ source types in Beijing from 2017 to 2018 in four seasons. The δ¹⁵N values of 212 NH₃ source samples were determined to build a local source profiles database of δ¹⁵N. NH₃ from traffic source presents significantly higher δ¹⁵N values (−14.0 ± 5.4‰), distinguished from other sources. The δ¹⁵N values of other sources besides traffic were more depleted and did not clear differences (solid waste, sewage, human feces, fertilizer, and livestock for −33.6 ± 4.5‰, −34.1 ± 4.8‰, −32.2 ± 3.8‰, −35.0 ± 3.9‰, and −34.9 ± 4.4‰, respectively). These sources were classified into non-traffic source in this study. From March 2018 to March 2019, ambient NH₃ samples were collected at an urban site in Beijing. With the newly developed source profiles in this study, the contribution of traffic and non-traffic sources to ambient NH₃ in an urban site in Beijing was calculated using ¹⁵N isotope mass balance equations. Traffic and non-traffic sources contributed 8% and 92% to ambient NH₃ in urban Beijing, respectively. The highest seasonal average contribution of traffic to ambient NH₃ was found in winter (22%). Our results reveal the importance of traffic source and provide evidence for the need to control NH₃ emission from traffic in urban Beijing in winter.

1 Introduction

Due to the intensive human activities of past decades, severe fine particle (PM_2.5) pollution occurred frequently in China, especially in the North China Plain (NCP). PM_2.5 pollution has known impacts on climate, visibility, radiation budget, and human health (Sun et al., 2006). It has been reported by previous studies that secondary inorganic aerosol (sulfate, nitrate, and ammonium) is a major contributor to PM_2.5 during haze periods (Huang et al., 2014; Tian et al., 2014). As the only alkaline gaseous precursor of PM_2.5 in the atmosphere, NH₃ plays an important role in PM_2.5 formation. NH₃ can neutralize acid species, such as nitric acid and sulfuric acid, forming secondary aerosols (Ansari and Pandis, 1998; Kirkby et al., 2011; Behera et al., 2013). Studies showed that NH₃ emissions have been increased since 1980 (Liu et al., 2013; Warner et al., 2017; Zhang et al., 2017), and the NCP was a hotspot area with high NH₃ concentration in China (Xu et al., 2015; Pan et al., 2018b). It has been proposed that reducing NH₃ could be a more effective method for haze mitigation in the NCP (Pan et al., 2016). Quantifying NH₃ emission sources and estimating the contribution from each key source in Beijing is not only urgent but also challenging.

NH₃ in the atmosphere is mainly emitted from anthropogenic sources, such as agricultural activities (fertilizer application and livestock manure), traffic, coal combustion, urban waste (like solid waste, sewage, and human feces), and biomass burning (Sutton et al., 2000; Behera et al., 2013; Chang, 2014; Li et al., 2017). It is widely accepted that livestock manure and fertilizer application are the most important sources of NH₃, accounting for approximately 60–80% to global NH₃ emission budget (Bouwman et al., 1997; Holland et al., 1999; Paulot et al., 2014; Liu et al., 2022). NH₃ emission source inventory over China suggested that agricultural source was the dominated source (Huang et al., 2012; Paulot et al., 2014; Kang et al., 2016; Zhang et al., 2017). Nevertheless, some studies argued that non-agricultural source could be underestimated in the urban area, which received increasing attention in recent years (Chang et al., 2016; Pan et al., 2016; Chang et al., 2019). There is still controversy over the source contribution of NH₃ in cities.

Stable nitrogen isotope composition (δ¹⁵N) here refers to the ratio of ¹⁵N/¹⁴N in NH₃ relative to atmospheric N₂ calculated in parts per thousand, which has been applied as an effective tool to identify NH₃ sources. Since NH₃ emitted from different sources have different δ¹⁵N values (Chang et al., 2016), sources of NH₃ at a site can be identified through the analysis of δ¹⁵N of ambient NH₃ and quantified further with the help of an isotope mixing model. According to published data, δ¹⁵N-NH₃ source signatures of coal combustions (−25.5 to −11.3‰) and urban traffic (−14.9 to 6.3‰) were found to be significantly different from agricultural sources, such as fertilizer application (−52.0 to −26.4‰) and livestock (−38.3 to −10.5‰) (Felix et al., 2013; Chang et al., 2016; Savard et al., 2017; Ti et al., 2018; Stratton et al., 2019; Bhattarai et al., 2020; Walters et al., 2020; Song et al., 2021). δ¹⁵N-NH₃ source signatures of urban waste, like solid waste (−36.6 to 7.8‰), sewage (−41.3 to −35.7‰), and human feces (−38.4 to −38.6‰) were reported to be similar to δ¹⁵N-NH₃ of agricultural sources (Chang et al., 2016; Liu et al., 2016).

Previous studies in some regions have reported the δ¹⁵N value of ambient NH₃ (Moore, 1977; Hayasaka et al., 2011; Buzek et al., 2017; Felix et al., 2017) and quantified the source of NH₃ or NH₄⁺ in particle using the isotope mixing model (Chang et al., 2016, 2019; Pan et al., 2016, 2018a; Ti et al., 2018). Since 2016, some reports on the source apportionment of NH₃ using δ¹⁵N-NH₃ have been published (Chang et al., 2016; Pan et al., 2016, 2018a; Bhattarai et al., 2020; Zhang et al., 2020; Gu et al., 2022), which helped researchers in reassessing the contribution of non-agricultural sources to NH₃ in urban Beijing. The accuracy of such estimation heavily relies on well-established source profiles of δ¹⁵N-NH₃. Localized source profiles, containing the δ¹⁵N-NH₃ signatures of traffic, urban waste, fertilizer application, and livestock have been reported in Shanghai, China (Chang et al., 2016), and Colorado, United States (Stratton, et al., 2019). Several studies published their results of δ¹⁵N-NH₃ values of traffic in Shenyang, China (6.3‰, Song et al., 2021), Albert, Canada (−14.9‰, n = 4, Savard et al., 2017), Providence, United States (6.6 ± 2.1‰, Walters et al., 2020), and Pittsburgh, United States (−4.6‰ and −2.2‰, Felix et al., 2013). For agricultural sources, δ¹⁵N-NH₃ values of fertilizer application in cropland was also measured in the Taihu area, China (−30.8 to −3.3‰), Maryland, United States (−48.0 to −36.3‰), and Alberta, Canada (−31.3‰). NH₃ emitted from livestock manure in the pig farm (−30.1 to −10.5‰), dairy farm (−28.5 to −11.3‰), cattle farm (−38.3%), and the turkey farm (−36.0 to −56.1‰) were reported in the Taihu area, China (Ti et al., 2018), Alberta, Canada (Savard et al., 2017), and Maryland, Kansas, and western Pennsylvania in the United States (Felix et al., 2013). There were not too many published data on δ¹⁵N-NH₃ values of urban waste. The δ¹⁵N-NH₃ values of agricultural sources like fertilizer application (−40.4 ± 5.3‰, Bhattarai et al., 2020) and livestock (−29.78 to −14.05‰, Liu et al., 2016), urban waste sources like landfill (−19.14 to 7.82‰, Liu et al., 2016) were measured in Beijing as well. The δ¹⁵N-NH₃ signatures, especially for urban waste were still relatively limited in Beijing.

The main goal of this research is to establish local δ¹⁵N-NH₃ source profiles in urban Beijing to carry out source apportionment of NH₃ in ambient air. The δ¹⁵N values of six NH₃ emission sources (traffic, solid waste disposal, sewage treatment, human feces disposal, fertilizer, and livestock) are reported in urban Beijing based on 212 NH₃ source samples. With the help of newly established source profiles, sources of ambient NH₃ were also identified and quantified at an urban site in Beijing.

2 Materials and Methods

2.1 Sampling

2.1.1 Sampling Sites

Except for the well-known NH₃ sources like fertilizer and livestock (Kang et al., 2016), non-agricultural NH₃ source samples (traffic, solid waste disposal, sewage treatment, and human feces disposal) were also sampled in urban Beijing in this study. For traffic source, some studies have shown the importance of traffic for NH₃ in the urban area (Sun et al., 2017). The emission inventory also suggests that urban waste (solid waste disposal, sewage treatment, and human feces disposal) could be important in cities with high-population density (Chang, 2014). Therefore, these sources were also included in this study.

NH₃ source samples were collected in four seasons from March 2017 to October 2018 at six sampling sites, including; 1) a crop site, located in the Shangzhuang experiment station, growing wheat in winter and corn in summer, and sampling was conducted at an acer of field where synthetic fertilizer was applied (120 kg N ha⁻¹) (Sha et al., 2020); 2) a livestock site, located in the Fengning experiment station, maintained about 4,000 pigs in average during the sampling period, and NH₃ samples were collected in three types of pig house (sow house, nursery house, and fattening house); 3) a traffic site, located in a 1,085 m-long Badaling tunnel, which is an ideal place to collect NH₃ emitted from vehicle exhaust, and emissions were from both gasoline cars and diesel vehicles including various personal and commercial vehicles; 4) two solid waste disposal sites, one site located in the Liulitun landfill, with the daily landfill volume as 887 tons in 2017 (NH₃ samples were collected at both the leachate treatment room and the landfill area), and the other was located in a solid waste transfer station in China Agricultural University; 5) a sewage treatment site, located in the Yongfeng sewage treatment plant, had a daily throughput of 1.98 × 10⁴ m³, and NH₃ samples were collected in a secondary sedimentation tank, oxidation ditch, and fine grid room; and 6) a human feces disposal site, located in the Sanxingzhuang human feces disposal station, had a daily fecal fluid throughput of 400 t, and NH₃ samples were collected in the fecal wastewater treatment tank and the fecal residue storage room. The locations of sampling sites are shown in Figure 1. More detailed information of sampling sites can be found in Supplementary Table S1.

FIGURE 1

FIGURE 1. The sampling locations of the NH₃ emission sources samples and ambient samples. The blue point indicates sites for collecting NH₃ source samples and the red pentagram shows the ambient air monitoring site.

In addition to source samples, ambient NH₃ samples were collected from March 2018 to March 2019. The monitoring site was set in the campus of Peking University (39°59′N, 116°18′E, PKU). It is a typical urban site in northwest of Beijing city, surrounded by residential buildings, teaching buildings, and parks, with dense population and traffic. There are no significant industrial emission sources near the site.

2.1.2 Sample Collection

In this study, the ALPHA passive sampler was used to collect NH₃ source samples and ambient NH₃ samples (Adapted Low-cost Passive High Absorption, CEH, Center for Ecology and Hydrology), which has been applied in many studies to measure NH₃ concentration and δ¹⁵N values (Tang et al., 2001; Skinner et al., 2004; Felix et al., 2013; Chang et al., 2016; Felix et al., 2017; Xu et al., 2017). The ALPHA sampler is a circular polyethylene vial (26 mm height, 27 mm diameter) with one open end, containing a 24 mm citric acid impregnated filter and a PTFE (Teflon) membrane for gaseous NH₃ diffusion (Supplementary Figure S1). The typical sampling duration for most NH₃ sources and ambient NH₃ was usually about 1 week. For livestock, NH₃ source sampling duration was 1 day. The sampling duration of the third sample of ambient NH₃ in June and the first ambient NH₃ samples in February 2019 were more than 2 weeks. The detection limit of ALPHA is 0.02 μg/m³.

At each site, the ALPHA sampling system (consisting of three ALPHA samplers) was placed at about 1.5 m above ground (ambient NH₃ samples were collected at 20 m above ground in the roof of a teaching building), and under a PVC shelter to prevent sampler from rain and sunlight (Supplementary Figure S1). A total of 212 NH₃ source samples and 45 ambient NH₃ samples were collected and analyzed in this study. To avoid contamination, the NH₃ absorbent was freshly prepared on the day of sampling. Collected NH₃ samples were stored at 4°C until analysis. Three field blanks were prepared for each batch of samples (about 50 samples). These field blanks were brought to each sampling site without installing on the sampler and then transported back to the laboratory. Along with NH₃ source samples and ambient NH₃ samples, NH₃ concentrations of field blanks were analyzed to assess potential contamination during laboratory preparation and sample transport between the field and the laboratory. All the concentration data reported in the following text were subtracted with blank.

2.2 Chemical Analysis

Before sampling, the filter was impregnated in the absorbent, which was made by citric acid dissolved in methanol. After sampling, NH₃ collected in the filter was extracted with ultrapure water (18.2 MΩ cm, Milli-Q system), and then analyzed as NH₄⁺ by using a continuous-flow analyzer (Seal AA3, Germany). The detection limit was 0.1 mgN/L. The analysis of NH₄⁺ concentration was conducted at the Key Laboratory of Plant–Soil Interactions, Chinese Ministry of Education, China Agricultural University.

The δ¹⁵N analysis was performed at the Stable Isotope Ecology Laboratory of Institute of Applied Ecology, Chinese Academy of Sciences, by following the method of Liu et al. (2014). First, NH₄⁺ in leaching liquor was oxidized to NO₂⁻ by BrO⁻, and then, NO₂⁻ was quantitatively converted into N₂O by reductant under strong acid condition. The performance of the reduction of NO₂⁻ to N₂O was evaluated by measuring the laboratory standard (NaNO₂, −11.7‰, determined by EA-IRMS). The produced N₂O was finally collected by a purge and cryogenic trap system (Gilson GX-271, IsoPrime Ltd., Cheadle Hulme, United Kingdom) and the δ¹⁵N values were determined on an IRMS (PT–IRMS) (IsoPrime 100, IsoPrime Ltd., Cheadle Hulme, United Kingdom). In this study, the first 119 source samples (collected from March 2017 to January 2018) were analyzed using hydroxylamine (NH₂OH) as the reductant. In order to shorten the conversion time of NO₂⁻ to NO₂ (from 16 h to 4 h), sodium azide (NaN₃) was used as reductant when the last 93 source samples (collected from March to October in 2018) and ambient samples were analyzed in the laboratory (Supplementary Table S1). There was no significant influence of isotopic fraction on isotope analysis for changing reductant because NO₂⁻ was fully quantitatively converted into N₂O by checking the measured δ¹⁵N value of laboratory NaNO₂ standards. Three international reference standards (IAEAN1, USGS25, and USGS26 with δ¹⁵N values of +0.4, −30.4, and +53.7‰, respectively) were used for calibration. The details of analytical procedures are also given elsewhere (Liu et al., 2014).

2.3 Calculation

The concentration of NH₃ (C, μg/m³) was calculated as follows:

$\text{C}=\left({\text{m}}_{\text{e}}-{\text{m}}_{\text{b}}\right)/\text{V},$

where m_e and m_b represent the amount of NH₃ (μg) collected on sample and blank sample, respectively; V is the effective sampled air volume (V, m³) by the ALPHA sampler, which is determined by the sampling time and the sampling rate of the sampler. V is calculated by the following equation:

$\text{V}=\text{DAt}/\text{L},$

where t represents the time of filter exposure to collect NH₃ gas (h); D is the diffusion parameter, D = 2.09 × 10⁻⁵ m²/s at 10°C; A represents the sampling area (m²) of the filter, A = 3.4636 × 10⁻⁴ m²; L is the diffusion length (m) from the membrane to the filter, L = 0.006 m.

The N isotope composition (δ¹⁵N) is reported in parts per thousand relative to atmospheric N₂ as follows:

${\text{δ}}^{15}N\left(\text{‰}\right)=\frac{{\left({}^{15}N/{}^{14}N\right)}_{sample}-{\left({}^{15}N/{}^{14}N\right)}_{standard}}{{\left({}^{15}N/{}^{14}N\right)}_{standard}}\times 1000,$

where ¹⁵N and ¹⁴N are the atomic mass of 15 and 14, respectively; ¹⁵N/¹⁴N represents the ratio of nitrogen isotope.

The calibration equation of δ¹⁵N is as follows:

${\text{δ}}^{15}{N}_{corrected}=\frac{{\text{δ}}^{15}{N}_{measured}-intercept}{slope},$

where δ¹⁵N_corrected is the corrected values of NH₃ sample; δ¹⁵N_measured is the measured values of NH₃ sample; the intercept and slope are from the linear regression of the measured δ¹⁵N values of standards and the assigned δ¹⁵N values of standards (Liu et al., 2014).

Only traffic source was significantly distinguished from other sources in the δ¹⁵N-NH₃ value, while sewage, solid waste, human feces, fertilizer, and livestock did not significantly differ from each other. Therefore, those sources that could not be significantly distinguished in δ¹⁵N-NH₃ values were lumped together as one category (non-traffic source). The contribution of traffic source and non-traffic source to ambient NH₃ can be calculated as follows:

$\begin{array}{l}{\text{δ}}^{15}{N}_{ambient}=f_{traffic}\times {\text{δ}}^{15}{N}_{traffic}+f_{non-traffic}\times {\text{δ}}^{15}{N}_{non-traffic}\\ f_{traffic}+f_{non-traffic}=1,\end{array}$

where δ¹⁵N_ambient is the observed values of ambient NH₃; δ¹⁵N_traffic, and δ¹⁵N_non-traffic are the measured values of NH₃ from traffic and non-traffic source; f_traffic and f_non-traffic are the contribution fraction of traffic and non-traffic source to ambient NH₃.

2.4 Statistical Analysis

To evaluate the differences in mean δ¹⁵N signatures and concentrations among NH₃ sources, one-way ANOVA followed by the Student–Newman–Keuls test (S–N–K) was carried out for post hoc multiple comparison at a 5% level of significance. One-way ANOVA was also used to determine any seasonal difference in mean δ¹⁵N-NH₃ signatures and concentrations among NH₃ sources and ambient NH₃. For traffic and fertilizer application, Kruskal–Wallis test was conducted to evaluate whether or not there is statistically significant difference between the medium values of δ¹⁵N values and NH₃ concentrations. The statistical analyses were performed using SPSS Version 25.0.

3 Results and Discussion

3.1 Source Profile of Ammonia Emission Source

3.1.1 Ammonia Concentration in Emission Sources

It can be seen that there is a wide range in NH₃ concentration among sources from 3.4 to over 8,000 μg/m³ (Figure 2). The highest average NH₃ concentration was found in the livestock farm (3,317.0 ± 2,316.0 μg/m³, n = 34), about 20 times and 70 times higher than human feces (102.3 ± 88.5 μg/m³, n = 50) and fertilizer (31.1 ± 50.3 μg/m³, n = 17), respectively. The mean concentration of NH₃ emitted from livestock was significantly different from other five sources (p < 0.05). Larger amount of urea, a kind of volatile nitrogen compound, in livestock and human feces could be responsible for high NH₃ concentration (Sha et al., 2020). In addition, NH₃ samples for livestock and fecal residue were collected indoor in this study, so the enclosed space resulted in high NH₃ accumulation. Large emission of NH₃ from urea fertilizer was also detected in this study. NH₃ concentration could reach up to 212.3 μg/m³ in the first 3 days after fertilizer application in corn field in summer. For solid waste disposal and sewage treatment (32.0 μg/m³ and 18.8 μg/m³, respectively), the mean concentration was lower than that in other sources. The average NH₃ concentration in traffic source was the third highest (47.2 μg/m³, n = 12), as the result of the large traffic volume and the semi-enclosed space in the tunnel. It also provides evidence that traffic could be an important source of NH₃.

FIGURE 2

FIGURE 2. The relationship between NH₃ concentration and δ¹⁵N-NH₃ values of each source samples in Beijing. (A) shows the δ¹⁵N-NH₃ values plotted against NH₃ concentration of each source samples. (B) shows the mean δ¹⁵N-NH₃ values and mean concentration of each sources, error bars indicate standard deviation of each mean. (C,D) are box-plots of δ15N‐ values and concentration of each sources respectively, the square and line within the box represent the mean and median values of δ¹⁵N‐NH₃ values and concentration, the left and right edges of the box represent the 25th and 75th percentiles of δ¹⁵N-NH₃ values and concentration, the left and right bars represent the min and max values, different letters adjacent the bars indicate difference among NH₃ sources (p < 0.05).

NH₃ concentration measured at pig barns in this study was similar to the results of other observations in China (2,369 μg/m³, n = 27, Beijing, Liu et al., 2016; 1,329.6 μg/m³, n = 4, Shanghai, Chang et al., 2016). It was about 20 times higher than that observed for cow and turkey (51.6–165.6 μg/m³, n = 7, Felix et al., 2013), since the ventilation of the pig farm in our sampling site is poor. For human feces disposal, NH₃ concentration was about 40 times lower than that determined in the septic tank (over 4,000 μg/m³, n = 8, Chang et al., 2016). In the study of Chang et al. (2016), large amounts of NH₃ accumulated in the enclosed septic tank results in higher NH₃ concentration, in contrast to less nitrogen compound after treatment in fecal residue and fecal wastewater in this study. In the perspective of fertilizer application, the average concentration of NH₃ collected in cropland for fertilizer application was close to that determined in the wheat field (27.5 μg/m³) but much lower than the rice field (99.3 μg/m³) (Ti et al., 2018). It is due to significantly higher NH₃ volatilization for rice paddy than wheat land (Huang et al., 2016).

NH₃ concentrations exhibited distinct seasonal variations for six sources (Supplementary Figure S2). In most sources, the concentration was higher in spring and summer than other seasons, especially winter. For solid waste disposal and sewage treatment, NH₃ concentration in spring and summer was statistically significantly different from fall and winter (p < 0.05). Significant difference was also found in fertilizer application. The mean concentration was significantly higher in summer than in spring (p < 0.05). The temperature could be a major influencing factor. Higher temperature in summer could enhance the NH₃ volatilization from emission source. However, livestock source exhibits different seasonal variation. The highest NH₃ concentration was found in winter (7,341.5 ± 1,689.7 μg/m³, n = 4) about seven times higher than the lowest concentration in summer (p < 0.05). In winter, all the windows were closed to maintain indoor temperature high and save energy. Since ambient temperature was high in summer, ventilation of pig houses was increased to help cooling, which favors NH₃ dispersion. It suggests that the ventilation could be an important influence factor for NH₃ concentration in the livestock site. Moreover, human activities might also affect NH₃ emission for some source type. For example, the residential water consumption would increase in summer, and the sewage treatment plant took on heavier treatment task. The monthly processing capacity of the Yongfeng sewage treatment plant was increased from about 450,000 m³ in June 2017 to 700,000 m³ in July 2017, which could also contribute to enhance NH₃ emission from sewage treatment source in summer.

3.1.2 δ¹⁵N-NH₃ Values From Major Sources

Figure 2 presents the range of δ¹⁵N-NH₃ values from NH₃ emission source samples (from −43.8 to −4.2‰). All these NH₃ source samples were depleted in ¹⁵N, exhibited with negative δ¹⁵N-NH₃ values. In general, there were no statistically significant differences among four seasons in δ¹⁵N-NH₃ values for all these six sources (Supplementary Figure S2). The NH₃ collected from traffic source has the highest δ¹⁵N-NH₃ values ranged from −21.3 to −4.2‰ with an average of −14.0 ± 4.9‰ (n = 12). It is significantly distinguished from other sources (p < 0.05) due to its relative abundance of ¹⁵N. NH₃ from fertilizer, livestock, solid waste, sewage, and human feces were more depleted in ¹⁵N and represented similar δ¹⁵N-NH₃ values (−35.0 ± 3.9‰, −34.9 ± 4.4‰, −33.6 ± 4.5‰, −34.1 ± 4.8‰, and −32.0 ± 4.6‰, respectively, see Table 1). These sources were most likely dominated by the process of NH₃ volatilization and appearing in similar and depleted δ¹⁵N-NH₃ values. It was also mentioned by Chang et al. (2016) and Stratton et al. (2019) before. Because of the kinetic isotopic fractionation associated with volatilization, lighter isotope (¹⁴NH₃) tends to volatilize more easily than heavier isotope (¹⁵NH₃). According to Melander and Saunders (1980), it almost always leads to the ¹⁵N enrichment in substrate and ¹⁵N depletion in product. So the NH₃ from volatile sources represented negative δ¹⁵N values.

TABLE 1

TABLE 1. δ¹⁵N values and NH₃ concentration of six NH₃ emission sources in Beijing.

The comparison between this study and previous reports are shown in Figure 3. The results in traffic source were similar to the tunnel observation in Shanghai and downwind monitoring in Albert (−14.2 ± 2.8‰, n = 8, Chang et al., 2016; −14.9‰, n = 4, Savard et al., 2017). Comparing with the observation in Colorado (−4.6‰ and 2.2‰, n = 2, Felix et al., 2013), the average δ¹⁵N-NH₃ values was lower in this study. Moreover, there is no significant difference in urban waste sources between this study and the observation conducted by Chang et al. (2016). Both Beijing and Shanghai are highly developed megacities with dense population and captured with relatively advanced waste treatment facilities. It could be responsible for the similar δ¹⁵N-NH₃ values.

FIGURE 3

FIGURE 3. Comparison of δ¹⁵N values for major NH₃ emission sources in this study to other studies.

However, livestock and fertilizer show different results from other studies. Overall, the δ¹⁵N-NH₃ values of livestock sampled in pig houses, ranging from −41.1 to −25.7‰ (n = 34) were relatively lower than other observations (Figure 3). For NH₃ volatilized from fertilizer application, results in this study (−39.5 to −27.1‰, n = 17) are similar to that reported in Canada (Savard et al., 2017). The observation in cropland is much higher than that conducted by Chang et al. (2016), since the results in this study represent the NH₃ emission in cropland while Chang et al. (2016) reported laboratory results. In addition, the difference could also be due to the difference in the NH₃ sampling method. It could be found from Figure 3 that NH₃ collected by passive samplers present lower δ¹⁵N values than active sampling systems. Passive samplers trap gaseous NH₃ through diffusion, and lighter ¹⁴NH₃ is more easily diffused and adsorbed by acid coating filters. It could lead to the lower δ¹⁵N-NH₃ values detected by the ALPHA sampler in this study. Skinner et al. (2006) reported similar results.

3.2 Concentration and δ¹⁵N Value of Ambient Ammonia

3.2.1 Concentration of Ambient Ammonia

From 26 March 2018 to 17 March 2019, the temporal variations of average concentration of ambient NH₃ are shown in Figure 4A. During the sampling period, the average concentration of NH₃ was 12.9 ± 6.0 μg/m³ (ranged from 3.6 to 25.1 μg/m³). The highest NH₃ concentration was found in 18-Jul-W2 (July 9 to 23, 2018), which was about eight times higher than the lowest determined in 18-Dec-W4 (December 24 to 31, 2018). Monthly trend of ambient NH₃ concentration is shown in Figure 4B. The average concentration of NH₃ increased month by month from March 2018 and reached the maximum in July 2018 (21.8 ± 4.9 μg/m³). Then it began to decrease and fell to the lowest in winter (6.1 ± 1.9 μg/m³, February 2019). Significant seasonal variation of NH₃ concentration could be found in Figure 4C. The average concentration of NH₃ in summer, spring, fall, and winter were 19.0 ± 4.5 μg/m³, 16.1 ± 5.4 μg/m³, 10.5 ± 2.2 μg/m³, and 6.6 ± 1.8 μg/m³, respectively. NH₃ concentration was relatively high in summer and spring and low in fall and winter. NH₃ emission from agricultural sources was enhanced in spring and summer, which had been reported in emission inventory (Huang et al., 2012; Kang et al., 2016). It could contribute to the higher NH₃ concentration. Ambient temperature had good correlation with NH₃ concentration (R = 0.768, p < 0.001), which could be an important meteorological factor for the seasonal variation of NH₃. Higher temperature could promote the NH₃ volatilization from soil, water, and emission sources like fertilizer and livestock (Ianniello et al., 2010).

FIGURE 4

FIGURE 4. Time series of ambient NH₃ concentration and δ¹⁵N values. (A) shows the concentration of weekly NH₃ samples. (B) shows the monthly average NH₃ concentration. (C) shows the average concentration of NH₃ in four seasons. (D) shows δ¹⁵N value and concentration of weekly NH₃ samples. (E) shows the monthly average of δ¹⁵N-NH₃ value. (F) shows the average δ¹⁵N-NH₃ value in four seasons. Different letters on the top of the error bars on (C) and (F) indicate significant difference in mean NH₃ concentration and insignificant difference in mean δ¹⁵N values among four seasons (p < 0.05).

Table 2 shows the comparison of concentration of ambient NH₃ between this study and previous observation. The NH₃ concentration in urban Beijing has no significant rise in recent years. The annual average concentration of NH₃ was close to previous reports using passive samplers (13.3 μg/m³, Zhang et al., 2018; 13.7 μg/m³, Pan et al., 2018b). The result in winter (18.2 μg/m³) reported by Zhao et al. (2016) was about three times higher than this study. Compared with the generally higher NH₃ concentrations in Chinese cities, there were relatively lower NH₃ concentrations in some developed regions (Table 2). NH₃ concentration in urban Beijing was higher than the urban sites in Spain (4.7 ± 2.1 μg/m³, Madruga et al., 2018; 3.9 ± 2.1 μg/m³, Reche et al., 2012) and the United States (1.8 μg/m³, nine sites in the United States, Felix et al., 2017). It suggests that NH₃ emission intensity in Beijing could be higher than these developed countries. In the three developing sites in Table 2, NH₃ concentration in Beijing was close to India and lower than Egypt. It also suggests that developing areas with more serious fine particle pollution and a higher NH₃ level should pay more attention to NH₃ reduction.

TABLE 2

TABLE 2. Comparison of concentration and δ¹⁵N values of ambient NH₃ concentration.

3.2.2 δ¹⁵N Value of Ambient Ammonia

From 26 March 2018 to 17 March 2019, the time series of the δ¹⁵N value of ambient NH₃ are shown in Figure 4D. In general, most of the data fell within the range of δ¹⁵N-NH₃ values of non-traffic sources. Ranging from −44.5 to −21.8‰, the mean δ¹⁵N values of ambient NH₃ was −32.7 ± 5.3‰. The mean δ¹⁵N-NH₃ values in summer (−30.4 ± 3.8‰) and winter (−30.9 ± 7.0‰) were slightly higher than spring (−35.3 ± 4.2‰) and fall (−33.4 ± 4.8‰). The δ¹⁵N-NH₃ values had no significant correlation with NH₃ concentration (R = 0.042, p = 0.782). It was also not correlated with ambient temperature in urban Beijing (R = −0.028, p = 0.855). In contrast to NH₃ concentration, no significant seasonal variation was found in δ¹⁵N-NH₃ values (Figure 4F).

In some weeks, the δ¹⁵N-NH₃ values was very deplete, and it even more depleted than the lowest δ¹⁵N-NH₃ values in the source profile (−43.8‰, in oxidation ditch, sewage treatment). N isotope fractionation could happen during the aerosol formation process, the collected NH₃ was not initial NH₃ mixing from sources. According to the previous study, aerosol formation could result in lower δ¹⁵N values of collected NH₃, compared to initial gaseous NH₃. The δ¹⁵N-NH₃ values could decrease from −5 to −20‰ in gaseous NH₃ and increase from +5 to +20‰ in aerosol through the process of aerosol formation (Heaton et al., 1997; Pan et al., 2018a). It could also be influenced by the volatilization from unstable ammonium particles (such as NH₄NO₃ and NH₄Cl). Another reason is that possible N isotope fractionation could also occur during long-range transport of air mass (Bhattarai et al., 2021). δ¹⁵N-NH₃ was also dependent on the fraction (f) of the total initial gaseous NH₃ converted to NH₄⁺ ion (NH₄⁺/(NH₄⁺+NH₃)) (Heaton et al., 1997). It confirmed that δ¹⁵N-NH₄⁺ increases with f value increases, and logically the δ¹⁵N value of unconverted NH₃ would be lower. In addition, potential source contribution function analysis (PSCF) was performed to explore the possible source region and transport distance of air mass in PKU site. The principle and calculation formulas of PSCF are shown in the Supplementary Text S1. The whole study period was divided into two groups for PSCF analysis: δ¹⁵N-NH₃ values lower than −33.7‰ (the mean value of non-traffic sources) and δ¹⁵N-NH₃ values higher than −33.7‰. According to the results of PSCF analysis, in both of two groups, most of the air masses were arriving from the southeast areas at the PKU site. For the weeks with more depleted δ¹⁵N-NH₃ values, weighted PSCF values in Beijing city and its surrounding areas (Supplementary Figure S3A) were much lower than other weeks (Supplementary Figure S3B). It suggested that local emission and short-range transport of air mass may contribute less to ambient NH₃ in the PKU site, while the long-range transport of air mass from further areas may has an influence on that during these weeks. N isotope fractionation happened with the long-range transport of air mass, resulting in more depleted δ¹⁵N-NH₃ values.

Table 3 shows the comparison of δ¹⁵N-NH₃ values between this study and previous reports. Compared with earlier studies using passive samplers, the determined δ¹⁵N-NH₃ values in this study are close to that conducted in urban Beijing (−35.0 ± 5.4‰, fall, Chang et al., 2016) and urban Shanghai (−31.7 ± 3.4‰, summer, Chang et al., 2019). However, it is lower than that reported from other foreign regions like the United States (−8.5 ± 7.2‰, Pittsburgh, Felix et al., 2014; −15.2‰, mean value in nine sites, Felix et al., 2017), Japan (−14.5 to −1.0‰, Hayasaka et al., 2011), and Czech Republic (−24.8 and −10.3‰, Buzek et al., 2017). It suggested that the source of NH₃ could be different in urban Beijing and foreign areas. Lower δ¹⁵N-NH₃ values in Beijing show NH₃ could more likely originate from non-traffic sources, while NH₃ in the United States could be more come from combustion-related source (like traffic). By the way, δ¹⁵N-NH₃ values in the urban site in Taihu areas (−23.0‰ to −5.1‰) were higher than this study in Beijing, even for the rural area (−24.2 to −3.0‰). One possible reason is the distinguished sampling methods between our studies. δ¹⁵N values of NH₃ collected by active sampling systems could be higher than the passive sampler (Pan et al., 2020). It could also result from the difference of meteorological condition between Beijing and Taihu areas. The annual temperature in Taihu areas is higher than that in Beijing, which was always higher than zero in winter (Ti et al., 2018).

TABLE 3

TABLE 3. Comparison of concentration and δ¹⁵N values of ambient NH₃ concentration and δ¹⁵N-NH₃ values.

3.3 Source Apportionment of Ambient Ammonia

To further quantify the contribution of sources to the NH₃ in ambient air in urban Beijing using newly developed pool of δ¹⁵N-NH₃ signature, isotope mixing equations was applied. The δ¹⁵N-NH₃ source profile shows that only traffic source was significantly distinguished with other sources in δ¹⁵N-NH₃ value. Others sources (sewage, solid waste, human feces, fertilizer, and livestock) did not significantly differ from each other. When the δ¹⁵N-NH₃ values of some sources could not be significantly distinguished, they could be pooled together to reduce the number of sources (Phillips and Gregg, 2003). Therefore, these sources with close δ¹⁵N-NH₃ values were pooled together as the non-traffic source in calculation. The average δ¹⁵N-NH₃ values for traffic source and non-traffic sources (−14.0‰, and −33.7‰) were served as the baseline input to the isotope mixing equation because the δ¹⁵N-NH₃ values of emission source shows no significant seasonal variation in this study.

The contribution of traffic source and non-traffic source to ambient NH₃ in each week during the monitoring campaign (from 26 March 2018 to 17 March 2019) is shown in Figure 5. In general, the annual average contribution of traffic and non-traffic source was 8 and 92%, respectively. It suggests that NH₃ mainly comes from non-traffic source during the whole monitoring campaign in the PKU site. Considering that in some weeks the δ¹⁵N-NH₃ values were lower than the average of non-traffic sources and without feasible solution, the mean source proportion was figured out by putting the annual average δ¹⁵N values into isotope mixing equation rather than calculating the average of weekly contribution. The weeks (19-Feb-W1 and 19-Mar-W3) in which δ¹⁵N-NH₃ values lower than lowest value (−43.8‰, in oxidation ditch, sewage treatment) were not included in calculation to minimize the influence of isotope fraction. The uncertainty was also assessed in this study. The standard error of source proportion was 4% for calculated source proportion of traffic and non-traffic sources. The uncertainty assessment in source apportionment was conducted by ISOERROR (v1.04), which takes the isotope values variability of both NH₃ sources and ambient NH₃ into consideration. The principle and calculation formulas of ISOERROR are shown in the Supplementary Text S2, more detailed information could be found in Phillips and Gregg (2001).

FIGURE 5

FIGURE 5. The contribution proportion of traffic source and non-traffic sources to ambient NH₃. (A) shows the δ¹⁵N-NH₃ value, NH₃ concentration, and PM_2.5 concentration. (B) shows the contribution of traffic source and non-traffic sources to ambient NH₃.

The traffic source proportion to ambient NH₃ in summer, fall, and winter was 17, 2, and 22%, respectively (the stand error was 9, 8, and 14%, respectively). Although the mean δ¹⁵N-NH₃ in spring had no satisfactory solution and then was removed, the comparison of the mean δ¹⁵N-NH₃ value could also help to evaluate NH₃ sources between spring and winter qualitatively. The mean δ¹⁵N-NH₃ value in spring (−35.3 ± 4.2‰, ranging from −29.8 to −44.5‰) was lower than that in winter (−30.9 ± 7.0‰, ranging from −21.8 to −45.3‰), suggesting that non-traffic source may contribute more to NH₃ at sampling site. Furthermore, part of samples in spring was still available to compare the contributions of traffic emissions to NH₃ between winter and spring (Figure 5B), in spite that the removal of data in spring might lead to an underestimate in the contribution of non-traffic NH₃ emission sources with low δ¹⁵N-NH₃. It shows that traffic contributed more to ambient NH₃ in winter and summer than other seasons at the PKU site. Due to agricultural timing, NH₃ emitted from agricultural sources was reduced in winter and enhanced in spring. Low temperature was also not conducive to the volatilization of NH₃ from sources in winter. So the calculated contribution proportion of traffic was increased in winter compared with spring. Specially in winter, NH₃ reduction should be paid more attention for haze mitigation,considering that haze happened more frequently in this season.

3.4 Estimation of Source Apportionment Results

The results of sources apportionment in this study were evaluated against the online monitoring of NH₃. From March 2018 to March 2019, continuous online monitoring (hourly temporal resolution) of ambient NH₃ was conducted by the In situ gas and aerosol composition monitoring system (IGAC, Model S-611, Fortelice International Co., Ltd.) at the PKU site at the same time. More detailed information of IGAC could be found in Young et al. (2016). Comparison of IGAC and ALPHA in NH₃ concentration was conducted. The hourly NH₃ concentration determined by IGAC was averaged to match the time resolution of ALPHA for comparison. The NH₃ concentration monitored by IGAC was close to ALPHA passive samplers, and good correlation was found between these two methods (Supplementary Figures S4, S5). The results of NH₃ concentration determined by ALPHA and IGAC in this study were credible. It also suggested that NH₃ samples collected by ALPHA were effective for further isotope analysis.

Previous studies showed that the diurnal NH₃ in the different source region had a distinct daily pattern (Wang et al., 2015). The diurnal NH₃ showed a bimodal cycle in the urban area and a single peak in the rural area. It suggests that NH₃ diurnal variation could help to distinguish the major source of NH₃. By calculating the mean NH₃ concentration observed by IGAC in each hour in a day, the NH₃ diurnal variations in four seasons during monitoring campaign are displayed in Supplementary Figure S6. To make sure the NH₃ diurnal drawn in this study could reveal the true trend of ambient NH₃ at the PKU site, only the days with more than 20 h effective hourly NH₃ concentration data were included in calculation. Distinct difference could be found between winter and other seasons. The single peak pattern (at 09:00–10:00) of NH₃ diurnal was found in spring, summer, and fall. Ambient temperature also shows similar diurnal trends to NH₃ concentration. It suggests NH₃ from volatile sources could play an important role in these seasons. In contrast, the NH₃ diurnal shows two peaks at 08:00–09:00 in the morning and 23:00–01:00 at the night in winter. It was consistent with traffic emission in Beijing. The NH₃ concentration peak at 23:00–01:00 could be caused by diesel trucks, because diesel trucks are only allowed to enter the fifth ring road from 23:00 at night to 6:00 the next day in Beijing. The significant difference of NH₃ diurnal between winter and other seasons suggests that the contribution of traffic to ambient NH₃ could increase in winter. It is consistent with the results by the isotope method.

Comparison between the calculated traffic contribution in this study and the results using NH₃ emission inventory was also conducted in this study. From November 2016 to March 2017, the monthly NH₃ emissions were compiled at a 1× 1 km grid by five sources (traffic, coal combustion, urban waste, fertilizer, and livestock) in the Beijing–Tianjin–Hebei region. To achieve reliable NH₃ emission calculation, native experiments results were considered and emission factors were parameterized by meteorological and other factors. More details of emission inventory could be found in previous studies (Huang et al., 2012; Kang et al., 2016). Considering that NH₃ is transported on a regional scale, the source analysis of NH₃ was based on the emission inventory in the Beijing–Tianjin–Hebei region. The emission inventory showed that the contribution of traffic, coal combustion, urban waste, fertilizer, and livestock were 15, 12, 5, 27, and 41%, respectively. From November 2018 to March 2019, the average δ¹⁵N values of NH₃ were −31.6‰, the calculated contribution of traffic and non-traffic source was 11 and 89%. In general, source apportionment results of two methods in traffic were close, suggesting that the results in this study were relatively reliable.

4 Conclusion

Our study reported the δ¹⁵N source profiles of NH₃ in urban Beijing for the first time, and the overall δ¹⁵N values of NH₃ sources were −14.0 ± 4.9, −35.0 ± 3.9, −34.9 ± 4.4, −33.6 ± 4.5, −34.1 ± 4.8, and −32.0 ± 4.6‰, for traffic, fertilizer, livestock, solid waste, sewage, and human feces, respectively. No significant seasonal variation of the δ¹⁵N signature of NH₃ from sources was found. The δ¹⁵N-NH₃ values of solid waste, sewage, human feces, fertilizer, and livestock (NH₃ volatilized from volatile nitrogen compound directly) were more depleted and overlapped, significantly different from that emitted from traffic. The mechanism of NH₃ formation could be a key influence factor of δ¹⁵N-NH₃ values.

In addition, the contribution of traffic and non-traffic sources to ambient NH₃ was quantified by using isotope mixing equation in urban Beijing from March 2018 to March 2019. The average contribution proportion of traffic and non-traffic sources was 8 and 92%, respectively. The contribution of traffic was increased in winter, with an average of 22%. The weekly contribution of traffic could reach to over 50%. The increased contribution of traffic to the ambient NH₃ during winter time indicating that control the NH₃ emitted from a vehicle exhaust could be meaningful to NH₃ reduction in urban Beijing.

There still exists uncertainty of source apportionment using δ¹⁵N. First, the δ¹⁵N-NH₃ values could not be significantly distinguished among fertilizer, livestock, sewage, solid waste, and human feces. Only the contribution of traffic and non-traffic sources could be figured out to a relatively reliable degree. Second, some potential sources (such as biomass burning, coal, and soil) were not involved in the source profile so far. δ¹⁵N of NH₃ emitted from the volatilization of ammonium particles was hard to determine. Thus, it is still important to make the current source profile more complete. Last, the isotope fraction could happen during aerosol formation and other process. How to determine the initial δ¹⁵N of mixed NH₃ from sources in ambient air is still an important task. Combining multiple methods could help to achieve more reliable source apportionment of NH₃ in the future.

Data Availability Statement

The observed data of NH₃ source profile are available on Supplementary Material at https://www.frontiersin.org/articles/10.3389/fenvs.2022.903013/full#supplementary-material. Publicly available datasets were analyzed in this study. These data can be found here: http://data.cma.cn/data/detail/dataCode/A.0012.0001.html.

Author Contributions

AT conceived and designed the project; MZ guided data analyses and manuscript writing; CW and XJL handled the field observation and laboratory experiments; CW and AT performed the data analyses and prepared the original draft; TZ and MC took part in the original draft writing; XM, YZ, XML, AT, MZ, and XJL reviewed and edited the manuscript; AT, MZ, and XJL were responsible for project administration and funding acquisition, and all authors joined result discussion and commented on the manuscript.

Funding

This work was financially supported by the National Natural Science Foundation of China (41730855, 42030708), the National Key R&D program of China (2016YFC0207906-1, 2017YFC0210101), and the High-level Innovative Talent Project of China Agricultural University.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

Special thanks go to Yu Song for providing the results of NH₃ emission inventory for the estimation of source apportionment results. The authors thank Zhipeng Sha and Tiantian Lv for their kind assistance in NH₃ source sampling and Yali Jin and Junyi Liu for their kind help in NH₃ online monitoring.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fenvs.2022.903013/full#supplementary-material

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