Vehicle emissions have been identified as an important urban source of ammonia (NH₃). However, there are large uncertainties regarding the contribution of vehicle emissions to urban NH₃ budgets, as well as the role of NH₃ in spatiotemporal fine particulate matter (PM_2.5) formation and nitrogen (N) deposition patterns. The N stable isotopic composition (δ¹⁵N) may be a useful observational constraint to track NH₃ emission sources and chemical processing, but previously reported vehicle δ¹⁵N(NH₃) emission signatures have reported a wide range of values, indicating the need for further refinement. Here we have characterized δ¹⁵N(NH₃) spatiotemporal variabilities from vehicle plumes in stationary and on-road measurements in the USA and China using an active NH₃ collection technique demonstrated to accurately characterize δ¹⁵N(NH₃) on the order of hourly time resolution. Significant spatial and temporal δ¹⁵N(NH₃) variabilities were observed and suggested to be driven by vehicle fleet composition and influences from NH₃ dry deposition on tunnel surfaces. Overall, a consistent δ¹⁵N(NH₃) signature of 6.6±2.1 ‰ ($\stackrel{\mathrm{‾}}{x}\pm \mathrm{1}\mathit{\sigma }$ ; n=80) was found in fresh vehicle plumes with fleet compositions typical of urban regions. Our recommended vehicle δ¹⁵N(NH₃) signature is significantly different from previous reports. This difference is due to a large and consistent δ¹⁵N(NH₃) bias of approximately −15.5 ‰ between commonly employed passive NH₃ collection techniques and the laboratory-tested active NH₃ collection technique. This work constrains the δ¹⁵N(NH₃) urban traffic plume signature, which has important implications for tracking vehicle NH₃ in urban-affected areas and highlights the importance of utilizing verified collection methods for accurately characterizing δ¹⁵N(NH₃) values.

New techniques have recently been developed and applied to capture reactive nitrogen species, including nitrogen oxides (${\mathrm{NO}}_x=\mathrm{NO}+{\mathrm{NO}}_{\mathrm{2}}$ ), nitrous acid (HONO), nitric acid (HNO₃), and particulate nitrate (p ${\mathrm{NO}}_{\mathrm{3}}^{-}$ ), for accurate measurement of their isotopic composition. Here, we report – for the first time – the isotopic composition of HONO from biomass burning (BB) emissions collected during the Fire Influence on Regional to Global Environments Experiment (FIREX, later evolved into FIREX-AQ) at the Missoula Fire Science Laboratory in the fall of 2016. We used our newly developed annular denuder system (ADS), which was verified to completely capture HONO associated with BB in comparison with four other high-time-resolution concentration measurement techniques, including mist chamber–ion chromatography (MC–IC), open-path Fourier transform infrared spectroscopy (OP-FTIR), cavity-enhanced spectroscopy (CES), and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF). In 20 “stack” fires (direct emission within ∼5 s of production by the fire) that burned various biomass materials from the western US, δ¹⁵N–NO_x ranges from −4.3 ‰ to +7.0 ‰, falling near the middle of the range reported in previous work. The first measurements of δ¹⁵N–HONO and δ¹⁸O–HONO in biomass burning smoke reveal a range of −5.3 ‰ to +5.8 ‰ and +5.2 ‰ to +15.2 ‰, respectively. Both HONO and NO_x are sourced from N in the biomass fuel, and δ¹⁵N–HONO and δ¹⁵N–NO_x are strongly correlated (R²=0.89, p<0.001), suggesting HONO is directly formed via subsequent chain reactions of NO_x emitted from biomass combustion. Only 5 of 20 p ${\mathrm{NO}}_{\mathrm{3}}^{-}$ samples had a sufficient amount for isotopic analysis and showed δ¹⁵N and δ¹⁸O of p ${\mathrm{NO}}_{\mathrm{3}}^{-}$ ranging from −10.6 ‰ to −7.4 ‰ and +11.5 ‰ to +14.8 ‰, respectively. Our δ¹⁵N of NO_x, HONO, and p ${\mathrm{NO}}_{\mathrm{3}}^{-}$ ranges can serve as important biomass burning source signatures, useful for constraining emissions of these species in environmental applications. The δ¹⁸O of HONO and ${\mathrm{NO}}_{\mathrm{3}}^{-}$ obtained here verify that our method is capable of determining the oxygen isotopic composition in BB plumes. The δ¹⁸O values for both of these species reflect laboratory conditions (i.e., a lack of photochemistry) and would be expected to track with the influence of different oxidation pathways in real environments. The methods used in this study will be further applied in future field studies to quantitatively track reactive nitrogen cycling in fresh and aged western US wildfire plumes.

Nitrous acid (HONO) is an important precursor to hydroxyl radical (OH) that determines atmospheric oxidative capacity and thus impacts climate and air quality. Wildfire is not only a major direct source of HONO, it also results in highly polluted conditions that favor the heterogeneous formation of HONO from nitrogen oxides (NO_x= NO + NO₂) and nitrate on both ground and particle surfaces. However, these processes remain poorly constrained. To quantitatively constrain the HONO budget under various fire and/or smoke conditions, we combine a unique dataset of field concentrations and isotopic ratios (¹⁵N $/$ ¹⁴N and ¹⁸O $/$ ¹⁶O) of NO_x and HONO with an isotopic box model. Here we report the first isotopic evidence of secondary HONO production in near-ground wildfire plumes (over a sample integration time of hours) and the subsequent quantification of the relative importance of each pathway to total HONO production. Most importantly, our results reveal that nitrate photolysis plays a minor role (<5 %) in HONO formation in daytime aged smoke, while NO₂-to-HONO heterogeneous conversion contributes 85 %–95 % to total HONO production, followed by OH + NO (5 %–15 %). At nighttime, heterogeneous reduction of NO₂ catalyzed by redox active species (e.g., iron oxide and/or quinone) is essential (≥ 75 %) for HONO production in addition to surface NO₂ hydrolysis. Additionally, the ¹⁸O $/$ ¹⁶O of HONO is used for the first time to constrain the NO-to-NO₂ oxidation branching ratio between ozone and peroxy radicals. Our approach provides a new and critical way to mechanistically constrain atmospheric chemistry and/or air quality models on a diurnal timescale.