Insight into the Variability of the Nitrogen Isotope Composition of Vehicular NOx in China

Refining δ15N isotopic fingerprints of local NOx for accurate source identification of nitrate in PM2.5

Stable nitrogen isotopic composition (δ15N) has proven to be a valuable tool for identifying sources of nitrates (NO3-) in PM2.5. However, the absence of a systematic study on the δ15N values of domestic NOx sources hinders accurate identification of NO3- sources in China. Here, we systematically determined and refined δ15N values for six categories of NOx sources in Tianjin using an active sampling method. Moreover, the δ15N values of NO3- in PM2.5 were measured during pre-heating, mid-heating and late-heating periods, which are the most heavily polluted in Tianjin. The results indicate that the isotopic fingerprints of the six types of NOx sources in Tianjin are indicative of the regional characteristics of China, particularly the North China Plain. The Bayesian isotope mixing (MixSIAR) model demonstrated that coal combustion, biomass burning, and vehicle exhaust collectively contributed more than 60 %, dominating the sources of NO3- during sampling periods in Tianjin. However, failure to consider the isotopic signatures of local NOx sources could result in an overestimation of the contribution from natural gas combustion. Additionally, the absence of industrial sources, an uncharacterized source in previous studies, may directly result in the contribution fraction of other sources being overestimated by the model more than 10 %. Notably, as the number of sources input to the model increased, the contribution of various NOx sources was becoming more stable, and the inter-influence between various sources significantly reduced. This study demonstrated that the refined isotopic fingerprint in China could more effectively distinguish source of NO3-, thereby providing valuable insights for controlling NO3- pollution.

Refined source apportionment of nitrate aerosols based on isotopes and emission inventories in coastal city of northern China

The increasing mass percentage of nitrate (NO3-) in PM2.5 in North China Plain (NCP) from 2013 (20.5 %) to 2019 (28.7 %) indicates that NO3- became the most prominent composition of atmospheric aerosols. However, accurately quantifying the sources of NO3- in aerosols remained questionable. In this study, we coupled dual isotopic composition of NO3- with multiple emission inventories during winter 2018 and summer 2019 to accurately identify the sources of NO3-. Source apportionment revealed that mobile sources (including road traffic and shipping) contributed 36.7 % to NO3-, followed by coal combustion (18.6 %), lightning (10.1 %), biomass burning (9.8 %), industry oil (8.8 %), natural gas (8.6 %), and soil (7.4 %) during summer. In winter, the contributions to NO3- shifted to mobile sources (39.6 %), coal combustion (32.3 %), biomass burning (12.0 %), natural gas (8.1 %), and industry oil (8.0 %). The contribution of major sources was consistent with regional emissions inventories, supporting us in further analyzing the contribution of regional emission. Marine air-mass contributed 33.7 ± 19.6 % of NO3- during summer. In winter, in addition to local emissions, regional transport from the Shandong area (outside Qingdao) and Beijing-Tianjin-Hebei (BTH) regions was particularly significant (62.2 ± 12.5 %). This study for the first time established a refined methodology for quantifying the contribution of emission sources and regional transport, providing basis for precise and effective control of the sustained increase of proportion of atmospheric NO3-.

Nitrogen isotope characteristics and importance of NOx from biomass burning in China

Biomass burning is a primary source of atmospheric nitrogen oxide (NOx), however, the lack of isotopic fingerprints from biomass burning limits their use in tracing atmospheric nitrate (NO3-) and NOx. A total of 25 biomass fuels from 10 provinces and regions in China were collected, and the δ15N values of biomass fuels (δ15N-biomass) and δ15N-NOx values of biomass burning (δ15N-NOx values of BB, open burning, and rural cooking stove burning) were determined. The δ15N-NOx values of open burning and rural cooking stove burning ranged from -0.8 ‰ to 11.6 ‰ and 0.8 ‰ to 9.5 ‰, respectively, indicating a significant linear relation with δ15N-biomass. Based on the measured δ15N-NOx values of BB and biomass burning emission inventory data, the δ15N-NOx values of BB in different provinces and regions of China were calculated using the δ15N-NOx model, with a mean value of 5.0 ± 1.8 ‰. The spatial variations in the estimated δ15N-NOx values of BB in China were mainly controlled by the differences in the δ15N-NOx values and the proportions of NOx emissions from various straw burning activities in provinces and regions of China. Furthermore, by using the combined local emissions of biomass burning with regional transportations of NOx based on air-mass backward trajectories, we established an improved δ15N-NOx model and obtained more accurate δ15N-NOx values of BB in regions (2.3 ‰ to 8.4 ‰). By utilising the reported δ15N-NOx values of precipitation and particulate matter from 21 cities in China and the more accurate δ15N-NOx values of BB, the NOx contributions from four sources (mobile sources, coal combustion, biomass burning, and microbial N cycle) at the national scale were estimated using a Bayesian model. The significant contributions of biomass burning (20.9 % to 44.3 %) to NOx emissions were revealed, which is vital for controlling NOx emissions in China.

Insights into anthropogenic impact on atmospheric inorganic aerosols in the largest city of the Tibetan Plateau through multidimensional isotope analysis

Particulate inorganic nitrogen aerosols (PIN) significantly influence air pollution and pose health risks worldwide. Despite extensive observations on ammonium (pNH4+) and nitrate (pNO3-) aerosols in various regions, their key sources and mechanisms in the Tibetan Plateau remain poorly understood. To bridge this gap, this study conducted a sampling campaign in Lhasa, the Tibetan Plateau's largest city, with a focus on analyzing the multiple isotopic signatures (δ15N, ∆17O). These isotopes were integrated into a Bayesian mixing model to quantify the source contributions and oxidation pathways for pNH4+ and pNO3-. Our results showed that traffic was the largest contributor to pNH4+ (31.8 %), followed by livestock (25.4 %), waste (21.8 %), and fertilizer (21.0 %), underscoring the impact of vehicular emissions on urban NH3 levels in Lhasa. For pNO3-, coal combustion emerged as the largest contributor (27.3 %), succeeded by biomass burning (26.3 %), traffic emission (25.3 %), and soil emission (21.1 %). In addition, the ∆17O-based model indicated a dominant role of NO2 + OH (52.9 %) in pNO3- production in Lhasa, which was similar to previous observations. However, it should be noted that the NO3 + volatile organic component (VOC) contributed up to 18.5 % to pNO3- production, which was four times higher than the Tibetan Plateau's background regions. Taken together, the multidimensional isotope analysis performed in this study elucidates the pronounced influence of anthropogenic activities on PIN in the atmospheric environment of Lhasa.

Quantification of NOx sources contribution to ambient nitrate aerosol, uncertainty analysis and sensitivity analysis in a megacity

Dual isotopes of nitrogen and oxygen of NO3- are crucial tools for quantifying the formation pathways and precursor NOx sources contributing to atmospheric nitrate. However, further research is needed to reduce the uncertainty associated with NOx proportional contributions. The acquisition of nitrogen isotopic composition from NOx emission sources lacks regulation, and its impact on the accuracy of contribution results remains unexplored. This study identifies key influencing factors of source isotopic composition through statistical methods, based on a detailed summary of δ15N-NOx values from various sources. NOx emission sources are classified considering these factors, and representative means, standard deviations, and 95 % confidence intervals are determined using the bootstrap method. During the sampling period in Tianjin in 2022, the proportional nitrate formation pathways varied between sites. For suburban and coastal sites, the ranking was [Formula: see text] (NO2 + OH radical) > [Formula: see text] (N2O5 + H2O) > [Formula: see text] (NO3 + DMS/HC), while the rural site exhibited similar fractional contributions from all three formation pathways. Fossil fuel NOx sources consistently contributed more than non-fossil NOx sources in each season among three sites. The uncertainties in proportional contributions varied among different sources, with coal combustion and biogenic soil emission showing lower uncertainties, suggesting more stable proportional contributions than other sources. The sensitivity analysis clearly identifies that the isotopic composition of 15N-enriched and 15N-reduced sources significantly influences source contribution results, emphasizing the importance of accurately characterizing the localized and time-efficient nitrogen isotopic composition of NOx emission sources. In conclusion, this research sheds light on the importance of addressing uncertainties in NOx proportional contributions and emphasizes the need for further exploration of nitrogen isotopic composition from NOx emission sources for accurate atmospheric nitrate studies.

Nitrate transformation and source tracking of rivers draining into the Bohai Sea using a multi-tracer approach combined with an optimized Bayesian stable isotope mixing model

Excessive levels of NO3- can result in multiple eco-environmental issues due to potential toxicity, especially in coastal areas. Accurate source tracing is crucial for effective pollutant control and policy development. Bayesian models have been widely employed to trace NO3- sources, while limited studies have utilized optimized Bayesian models for NO3- tracing in the coastal rivers. The Bohai Rim is highly susceptible to ecological disturbances, particularly N pollution, and has emerged as a critical area. Therefore, identification the N fate and understanding their sources contribution is urgent for pollution mitigation efforts. In addition, understanding the influenced key driven factors to source dynamic in the past ten years is also implication to environmental management. In this study, water samples were collected from 36 major river estuaries that drain into the Bohai Sea of North China. The main transformation processes were analyzed and quantified the sources of NO3- using a Bayesian stable isotope mixing model (MixSIAR) with isotopic approach (δ15N-NO3- and δ18O-NO3-). The overall isotopic composition of δ15N-NO3- and δ18O-NO3- in estuary waters ranged from -0.8-19.3‰ (9.3 ± 4.6‰) and from -7.1-10.5‰ (5.0 ± 4.3‰), respectively. The main sources of nitrate in most river estuaries were manure & sewage, and chemical fertilizer, while weak denitrification and mixed processes were observed in Bohai Rim region. A temporal decrease in the nitrogen load entering the Bohai Sea indicates an improvement in water quality in recent years. By incorporating informative priors and utilizing the calculated coefficients, the accuracy of sourcing results was significantly improved. This study highlighted the optimized MixSIAR model enhanced its accuracy for sourcing analysis and providing valuable insights for policy formulation. Future efforts should focus on improving management strategies to reduce nitrogen into the bay.

Quantifying the Nitrogen Sources and Secondary Formation of Ambient HONO with a Stable Isotopic Method

Nitrous acid (HONO) is a reactive gas that plays an important role in atmospheric chemistry. However, accurately quantifying its direct emissions and secondary formation in the atmosphere as well as attributing it to specific nitrogen sources remains a significant challenge. In this study, we developed a novel method using stable nitrogen and oxygen isotopes (δ15N; δ18O) for apportioning ambient HONO in an urban area in North China. The results show that secondary formation was the dominant HONO formation processes during both day and night, with the NO2 heterogeneous reaction contributing 59.0 ± 14.6% in daytime and 64.4 ± 10.8% at nighttime. A Bayesian simulation demonstrated that the average contributions of coal combustion, biomass burning, vehicle exhaust, and soil emissions to HONO were 22.2 ± 13.1, 26.0 ± 5.7, 28.6 ± 6.7, and 23.2 ± 8.1%, respectively. We propose that the isotopic method presents a promising approach for identifying nitrogen sources and the secondary formation of HONO, which could contribute to mitigating HONO and its adverse effects on air quality.

Application of Stable Isotope Techniques in Tracing the Sources of Atmospheric NOX and Nitrate

Nitrate is an important component of PM2.5, and its dry deposition and wet deposition can have an impact on ecosystems. Nitrate in the atmosphere is mainly transformed by nitrogen oxides (NOX = NO + NO2) through a number of photochemical processes. For effective management of the atmosphere’s environment, it is crucial to understand the sources of atmospheric NOX and the processes that produce atmospheric nitrate. The stable isotope method is an effective analytical method for exploring the sources of NO3− in the atmosphere. This study discusses the range and causes of δ15N data from various sources of NOX emissions, provides the concepts of stable isotope techniques applied to NOX traceability, and introduces the use of Bayesian mixture models for the investigation of NOX sources. The combined application of δ15N and δ18O to determine the pathways of nitrate formation is summarized, and the contribution of Δ17O to the atmospheric nitrate formation pathway and the progress of combining Δ17O simulations to reveal the atmospheric oxidation characteristics of different regions are discussed, respectively. This paper highlights the application results and development trend of stable isotope techniques in nitrate traceability, discusses the advantages and disadvantages of stable isotope techniques in atmospheric NOX traceability, and looks forward to its future application in atmospheric nitrate pollution. The research results could provide data support for regional air pollution control measures.

Nitrogen isotopic composition of NOx from residential biomass burning and coal combustion in North China

Stable nitrogen isotope (δ¹⁵N) technology has often been used as a powerful tool to separate nitrogen oxides (NO_x) produced by residential combustion (i.e., biomass burning and coal combustion) from other sources. However, the insufficient measurement of δ¹⁵N-NO_x fingerprints of these emissions limits its application, especially in North China where residential emissions are significant. This study conducted combustion experiments to determine the δ¹⁵N-NO_x of typical residential fuels in North China, including ten biomass fuels and five types of coal. The results showed that the δ¹⁵N of biomass varied between -6.9‰ and 2.3‰, which was lower than the δ¹⁵N of residential coal (-0.2‰-4.6‰). After combustion, the δ¹⁵N of biomass residues increased greatly, while that of coal residues showed no significant upward trend (p > 0.05). The δ¹⁵N-NO_x produced by biomass burning ranged from -5.6‰ to 3.2‰ (-0.4‰ ± 2.4‰), showing a significant linear relation with δ¹⁵N-biomass. Comparatively, the δ¹⁵N-NO_x derived from residential coal combustion was much higher (16.1‰ ± 3.3‰), ranging from 11.7‰ to 19.7‰. It was not well correlated with δ¹⁵N-coal, and only slightly lower than the estimated δ¹⁵N-NO_x of industrial coal combustion (17.9‰, p > 0.05). These observations indicate that the δ¹⁵N-NO_x of residential coal combustion is a result of the mixture of thermal- and fuel-released NO_x. Based on the isotopic characteristics observed in this study, we analyzed the reported δ¹⁵N-NO_x, and provided more statistically robust δ¹⁵N-NO_x distributions for biomass burning (1.3‰ ± 4.3‰; n = 101) and coal combustion (17.9‰ ± 3.1‰; n = 26), which could provide guidance for scientific studies aiming to quantify the origin of NO_x in North China and in other regions.

Stable nitrogen isotope composition of NOx of biomass burning in China

Owing to the local characteristics of stable nitrogen isotopes in nitrogen oxides (δ¹⁵N-NO_x) emitted from biomass burning, the lack of data on δ¹⁵N-NO_x values associated with biomass burning in China limits the use of this parameter in identifying and quantifying the sources of atmospheric nitrate (NO₃^-) and NO_x. The results showed that the δ¹⁵N-NO_x values of open burning and rural cooking stoves in China ranged from -3.7‰ to 3.1‰ and -11.9‰ to 1.5‰, respectively. The δ¹⁵N values of nine biomass fuel sources (δ¹⁵N-biomass) ranged from 0.1‰ to 4.1‰. Significant linear relationships between the δ¹⁵N-biomass values and δ¹⁵N-NO_x values of open burning (δ¹⁵N-NO_x = 1.1δ¹⁵N-biomass - 2.7; r² = 0.63; p < 0.05) and rural cooking stoves (δ¹⁵N-NO_x = 1.7δ¹⁵N-biomass - 9.8; r² = 0.72; p < 0.01) suggested that the variations in δ¹⁵N-NO_x values from biomass burning were mainly controlled by the biomass fuel source. The isotopic fractionation of nitrogen during the biomass burning process might have led to the higher δ¹⁵N-NO_x values from open burning in comparison to rural cooking stoves. By combining the δ¹⁵N-NO_x values of biomass burning with biomass burning emission inventory data, a model for calculating the δ¹⁵N-NO_x values of biomass burning in different regions of China was established, and the estimated δ¹⁵N-NO_x value of biomass burning at the national scale was -0.8 ± 1.2‰. But the limited δ¹⁵N-biomass values increase the uncertainty of model in national scale.

Dual-isotope-based source apportionment of nitrate in 30 rivers draining into the Bohai Sea, north China

Excessive nitrate (NO₃^-) in rivers can lead to water quality deterioration, and can also be directly input into estuaries and oceans, thus posing a serious threat to the stability of their ecosystems. In this study, the concentration, isotopes and sources of NO₃^- in 30 rivers discharging into the Bohai Sea were comprehensively investigated. The mean concentration of NO₃^--N was 2.24 ± 2.11 mg L^-1, with obvious seasonal and spatial variations. In total, 104.24 kt of NO₃^--N was discharged into the Bohai Sea annually, to which the Yellow River Basin and Liao River Basin made the largest contributions. The range of δ¹⁵N-NO₃^- was -1.1‰ to +33.2‰ (mean value, +11.4 ± 5.0‰), with no significant seasonal or spatial differences; the mean value of δ¹⁸O-NO₃^- was +9.4 ± 7.2‰, with much higher values seen in June. Based on the MixSIAR model, manure (24.3 ± 7.5%) and sewage (19.1 ± 14.5%) were the primary sources of NO₃^- in the 30 rivers, followed by NO₃^- fertilizers (16.3 ± 12.5%), soil N (15.5 ± 11.9%), atmospheric deposition of NO₃^- (13.5 ± 5.7%) and NH₄⁺ fertilizers (11.4 ± 8.9%). This finding highlights the vital roles of sewage and manure management in riverine NO₃^-. Using a mathematical method, the contributions of various sources to each river were simulated. The results indicated that management of the Yellow River, Daliao River, Liao River, and Xiaoqing River is more urgently needed than that of other rivers to control Bohai NO₃^- pollution. We believe that this finding will provide guidance for scientific management of NO₃^- pollution in these 30 rivers and the Bohai Sea.