Next Article in Journal
On the Mechanical and Thermodynamic Influences of Ocean Spray in Hurricane Boundary Layers
Previous Article in Journal
Estimating Effect of Sheltering on Horizontal Measurement of Global Solar Radiation Using a Pyranometer
Previous Article in Special Issue
Preliminary Study of the Isotopic Characteristics of Atmospheric Ammonia at a Coal Coking Industrial Park in Taiyuan, China, Using OGAWA Sampling
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Atmosphere
Volume 17
Issue 6
10.3390/atmos17060558
atmosphere-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Impacts from HONO Chemistry on Atmospheric Oxidation Capacity: A Case Study in Shanghai

by
Wei Zhang
1,
Ming Hu
1,2,
Jialiang Feng
1,
Qingyan Fu
3,* and
Shunyao Wang
1,*
1
School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
2
Shanghai Environmental Monitoring Center, Shanghai 200235, China
3
State Environmental Protection Key Laboratory of the Cause and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
*
Authors to whom correspondence should be addressed.
Atmosphere 2026, 17(6), 558; https://doi.org/10.3390/atmos17060558
Submission received: 18 April 2026 / Revised: 15 May 2026 / Accepted: 26 May 2026 / Published: 29 May 2026
(This article belongs to the Special Issue Air Pollution: Emission Characteristics and Formation Mechanisms)
Browse Figures
Versions Notes

Abstract

Nitrous acid (HONO) plays a vital role in atmospheric oxidation capacity (AOC) and ozone (O3) formation. Based on 2017–2021 observations at urban Pudong (PD) and suburban Qingpu (QP) in Shanghai, HONO concentrations ranged from 0.74 ± 0.45 to 1.38 ± 0.52 ppb in PD and 0.82 ± 0.50 to 1.19 ± 0.62 ppb in QP, with higher levels in summer and a typical morning peak at 8–9 a.m. HONO photolysis produced an average of 1.9 ppb h−1 of OH in summer, significantly elevating AOC. Under HONO constraints, summer O3 production rates via HO2 + NO and RO2 + NO increased by 16% and 20%, respectively. These results highlight the key contribution of HONO chemistry to photochemical pollution and provide implications for air quality control in the Yangtze River Delta.

1. Introduction

Nitrous acid (HONO) is a key reactive nitrogen species that plays a crucial role in atmospheric oxidation chemistry, climate change, air quality and human health [1,2,3]. Its photolysis (Equation (1)) is recognized as a major primary source of hydroxyl radical (OH). The ambient HONO concentration is regulated by a complex balance between its sinks and sources. The dominant sinks involve photolysis, dry and wet deposition, and gas-phase reactions with the OH radical (Equation (4)) [4,5,6]. HONO formation pathways are traditionally classified into three main categories, including direct emissions (e.g., vehicle exhaust), homogeneous reactions (Equation (2)) [7], and heterogeneous reactions (Equation (3)) [8,9,10,11,12,13,14,15]. Other reactions, such as HONO with HNO3 (Equation (5)), are generally considered to play a relatively minor role due to their slow kinetics [16].
HONO + hv → NO +·OH
NO + OH → HONO
HNO3 (ads)/NO3 (ads) + hv → HONO
HONO +·OH → NO2 + H2O
HONO + HNO3 → 2NO2 + H2O
The photolysis of HONO is particularly important as a dominant early-morning source of OH radical, initiating daytime photochemistry. Because HONO accumulates during the night and photolyzes rapidly after sunrise, it acts as the primary radical initiator in the early morning when other traditional sources, such as ozone photolysis, are negligible [17,18]. This early-morning burst of OH radical effectively starts daytime photochemistry, accelerating the oxidation of volatile organic compounds (VOCs) and shifting the peak of secondary pollutant formation earlier in the day, thereby significantly enhancing the atmospheric oxidation capacity (AOC). Beyond its role as a morning initiator, HONO photolysis serves as a sustained source of OH throughout the day, often competing with or even surpassing O3 photolysis in polluted urban boundary layers [19,20]. This efficiency is attributed to its broad absorption cross-section at longer wavelengths (up to 400 nm), which allows HONO to undergo photolysis under lower solar intensity compared to the shorter wavelengths (<330 nm) required for O3 photolysis [21]. Consequently, the OH radical produced from HONO directly fuels the HOx (OH + HO2) and ROx (RO + RO2) radical cycles, acting as a catalyst that sustains the chain reactions of atmospheric oxidation even under sub-optimal light conditions [22,23]. This makes HONO a critical precursor controlling the formation of secondary pollutants, including ozone (O3) and secondary organic aerosol (SOA) [24,25]. The contribution of HONO to OH production exhibits strong temporal and spatial variability. Typically, HONO photolysis leads to a pronounced morning peak in OH levels, while seasonal variations are driven by solar radiation intensity, with higher OH production in summer than in winter [24,26].
O3 formation is driven by complex photochemical reactions involving volatile organic compounds (VOCs) and nitrogen oxides (NOx) [27]. As a major precursor of OH radical, HONO indirectly influences O3 formation by accelerating the oxidation of NO to NO2 through HO2 and RO2 radicals, thereby enhancing photochemical O3 production cycles [28]. The impact of HONO on O3 has been previously assessed using various atmospheric models. Liu et al. [29] systematically assessed the potential impacts from HONO on O3 production using a 0-dimensional model based on field data during summer, which found the default mode in the model (which includes only NO + OH reactions) underestimates observed HONO levels by ~87%, leading to a significant decrease in net O3 production in the morning (~19%). In another study, Ye et al. [30] reported that adding HONO as the model constraint can result in 88% increase in the mean peak of net ozone production rate compared to the scenario without constraints from HONO. Furthermore, 8–70% increases in O3 concentrations were observed following the introduction of HONO into the model framework of WRF-CMAQ (Weather Research and Forecasting Community Multiscale Air Quality Modeling System) [4,31,32].
Ambient HONO concentrations show substantial spatial variability worldwide. In urban areas, HONO mixing ratios typically range from 0.5 to 5 ppb, while lower levels (generally <1 ppb) are observed in rural and remote regions [33]. In China, especially in megacities such as Beijing, Shanghai, and Guangzhou, elevated HONO levels have frequently been reported due to intense anthropogenic emissions and favorable heterogeneous conversion conditions [34,35]. Over the past few decades, the pollution characteristics and evolutionary pathways of HONO have been scrutinized globally at diverse observation sites. Within China, the majority of research has focused on the Yangtze River Delta (YRD), the North China Plain (NCP), and the Pearl River Delta (PRD) [36,37,38]. Early paradigms suggested that HONO accumulation during haze episodes primarily stemmed from the homogeneous gas-phase reaction between NO and OH radical [28]. Nevertheless, subsequent findings have highlighted the pivotal, and often predominant, role of NO2 heterogeneous reactions [39,40]. For instance, in Nanjing, multiphase NO2 conversions on aerosol and ground surfaces contributed 40% and 36% to total HONO production, respectively [41]. These studies highlight the importance of HONO in driving regional atmospheric oxidation and secondary pollution formation.
Accurate quantification of atmospheric HONO remains a technical challenge. Measurement methodologies primarily fall into two categories: spectroscopic methods (e.g., DOAS, CRDS) and wet-chemical methods (e.g., LOPAP, MARGA). Among these, LOPAP is widely regarded as a reliable technique due to its high sensitivity and selectivity, while DOAS provides path-integrated measurements suitable for field observations and MARGA is highly sensitive for long-term continuous monitoring [42,43]. However, discrepancies among different measurement techniques still exist, contributing to uncertainties in HONO budgets and source apportionment.
Despite significant improvements in air quality following the implementation of clean air policies in China, ozone pollution remains a critical issue in many urban regions [44,45]. However, long-term observations and comprehensive analyses of HONO chemistry are still limited, particularly in the YRD region. In this study, a multi-year (2017–2021) observational dataset of HONO, combined with aerosol composition and meteorological parameters, was used to investigate the role of HONO in regional atmospheric oxidation capacity in Shanghai. This work provides new insights into the mechanisms of HONO formation and its implications for future air pollution control strategies in the YRD region.

2. Materials and Methods

2.1. Site Description

This study selected two observation sites in Shanghai—Pudong and Qingpu—as sampling locations to collect data on HONO, PM2.5 and its components, other gaseous pollutants, and meteorological parameters. The Pudong observation (PD) point (121.533° E, 31.228° N) is located within the Inner Ring Road of downtown Shanghai, surrounded by residential and commercial areas. The sampling point is approximately 20 m above ground level and is representative of Shanghai’s densely populated urban areas. The Qingpu observation (QP) site (120.989° E, 31.097° N) is situated at the junction of Shanghai, Jiangsu, and Zhejiang provinces. This location represents a suburban environment; the sampling point is also approximately 20 m above ground level and is surrounded by extensive vegetation and Dian Shan Lake. It is worth noting that both observation sites are located in the eastern part of the Yangtze River Delta region, which has a subtropical monsoon climate. An overview of the two observation sites is shown in Figure 1.

2.2. Measurement of Air Pollutants

HONO, PM2.5 composition, other gaseous pollutants, and meteorological parameters were continuously monitored at an urban site, PD, and a suburban site, QP, in Shanghai from 2017 to 2021. PM2.5 was collected using a PM2.5 sampler (Tisch TE-6070, Cleves, OH, USA) with a flow rate of 1.13 m3 min−1 and a quartz fibre filter (QM-A, 20.0 cm × 25.4 cm, Whatman, Maidstone, UK). Gaseous pollutants (HONO, HNO3, HCl, SO2, and NH3) and water-soluble aerosol ions (NO3−, SO42−, Cl−, Na+, NH4+, K+, Mg2+, and Ca2+) were measured online with a time resolution of 1 h using an ambient air aerosol and gas monitor (MARGA ADI 2080, Applikon Analytical B.V., Metrohm, Herisau, Switzerland). The operating principle of MARGA is briefly described as follows: Ambient air passes through a 2.5 μm particle size impactor at a flow rate of 16.7 L min−1. The air stream first passes through a wet rotary dissolver (WRD), where gaseous pollutants are absorbed by a 0.0035% H2O2 solution via diffusion, and then particles are collected by a steam jet aerosol collector (SJAC). The absorbent is drawn from the WRD and SJAC into a syringe and then injected into an ion chromatograph (IC; for cations, a Metrosep C4-100/4.0 column and a 3.2 mmol L−1 CH3SO3H eluent are used; for anions, a Metrosep A Supp 10–75/4.0 column and a 7.0 mmol L−1 Na2CO3 + 8.0 mmol L−1 NaHCO3 eluent, with H3PO4 as a suppressant). Ion analysis was performed hourly using an internal standard (LiBr). At the same time, our previous study compared HONO measurements from MARGA with those obtained during the same period in Yangpu, Shanghai, using a long-path absorption photometer (LOPAP) (QUMA, Model LOPAP-03, QUMA Elektronik & Analytik, Wuppertal, Germany). The HONO data from MARGA were consistent with the data and trends observed in Yangpu during that period [46,47]. VOCs (e.g., C2H6, C2H2, benzene, toluene, 2-butene, etc.) were analyzed using a PerkinElmer 300TD VOC (PerkinElmer, Shanghai, China) at the PD site, and Chromatotec A1100 (Chromatotec, Beijing, China) was used at the QP site. Due to limitations in monitoring conditions, we were unable to detect the key data point of HCHO. Ambient air samples were collected and analyzed with a dual-capture and dual-separation configuration, achieving a time resolution of 1 h. Hydrocarbons ranging from C2 to C5 were analyzed qualitatively and quantitatively using a flame ionization detector (FID, Norwalk, CT, USA), while hydrocarbons, halogenated hydrocarbons, and oxygenated compounds from C5 to C12 were analyzed using mass spectrometry (MS). O3, NOx, and SO2 were measured by O3, NOx, and SO2 analyzers (Models 49i, 42i and 43i, Thermo Fisher Scientific, Waltham, MA, USA), respectively. Specific QA/QC details, including detection limits, precision, accuracy, blank corrections, and known daytime chemical interferences of the MARGA system, are detailed in Text S1.

2.3. Photochemical Box Modeling

The Framework for 0-D Atmospheric Modelling (F0AM v4.2.2), integrated with the Master Chemistry Mechanism (MCM v3.3.1) is used to simulate the 1. HONO sources and sinks; 2. diurnal distributions of OH chemical budgets with and without HONO constraints; and 3. diurnal distributions of O3 chemical budgets with and without HONO constraints at both sites in Shanghai. The simulation accounts for deposition and dilution/mixing within the planetary boundary layer (PBL) [48]. The simulation results were constrained by the use of O3, NO, NO2, CO, and VOC species and meteorological parameters, including temperature (T), relative humidity (RH), pressure (P), and PBL. The data for all inputs is read at one-hour intervals. The dilution of air pollutants through various processes such as deposition and transport is simply represented in the model using a first-order dilution function, with a dilution rate constant of 1/24 h−1. We parameterized the heterogeneous HONO formation pathways in a box model based on recent field observations and laboratory experiments [49,50,51].
OH in the atmosphere is crucial for the budget of HONO sources and sinks. Since this study did not directly monitor OH mixing ratios, the concentration of OH radical was estimated using an empirical function based on the relatively stable relationship between OH and J (O1D) [52] (Equation (6)).
O H = a × ( J O 1 D 10 − 5 s − 1 ) b + c
Here, a and b are 4.2 × 106 cm−3 and 1.0, respectively. The value of c is 0.2 × 106 cm−3 in winter and 1 × 106 cm−3 in summer [53]. In this study, the diurnal peak of OH mixing ratio for the selected period ranged between 2–10 × 106 molecules cm−3, which is comparable to the OH mixing ratio measured in polluted areas of China (1–10 × 106 molecules cm−3) [34].
Particle surface area is an important parameter for studying the heterogeneous formation of HONO associated with aerosol. In this study, the aerosol surface area was not directly measured on-site, but was estimated based on the linear relationship between PM2.5 mass concentration and surface area measured at the QP site from 2018 to 2019 [51]. Subsequently, the surface area of wet particles was corrected according to the composition-based kappa function under specific relative humidity conditions and the kappa-Köhler relationship, and then input into a photochemical box model to simulate aerosol-associated heterogeneous HONO formation pathways (Text S2).
The default MCM v3.3.1 mechanism does not include heterogeneous HONO formation pathways. Therefore, based on recent field observations and laboratory experiments, we parameterized these processes in the box model (Text S3, Tables S1 and S2).

3. Results

3.1. Annual Trend of HONO in Shanghai

The seasonal variation of HONO in different years is demonstrated in Figure 2a,b, which illustrates that the seasonal mean concentrations in PD ranged from 0.74 ± 0.45 (spring 2020) to 1.38 ± 0.52 ppb (summer 2021). The spring concentrations in 2019 were slightly higher compared to other years, which may be influenced by local emissions or meteorological conditions. The seasonal mean concentrations in QP ranged from 0.82 ± 0.50 (spring 2020) to 1.19 ± 0.62 ppb (autumn 2018). The data indicate that the trends in HONO concentrations in PD and QP are consistent and that the seasonal variations observed in PD and QP are not statistically significant, with relatively high levels of HONO in the summer compared to the other three seasons. The lower HONO values for PD in the summer of 2018 and QP in the summer of 2019 are due to a lack of data for these two periods. Conversely, the reduced HONO concentrations observed in spring 2020 for both PD and QP may be attributable to the decline in pollutant emissions during the epidemic. The elevated HONO levels detected in summer could be attributed to light-induced heterogeneous transformation of surface NO2 molecules, which subsequently led to increased HONO production. Overall HONO concentrations were higher at the QP site than at the PD site, suggesting that there may have been additional sources of HONO (e.g., soil releases or traffic emissions) in the suburb during certain periods. Additionally, direct emissions from surface soils have also been identified as a contributing factor to HONO production [41]. Meteorological conditions such as temperature, humidity, and sunlight intensity can affect HONO levels [38,54,55]. Higher summer temperatures and intense sunlight can enhance photochemical reactions, leading to higher HONO concentration [56].
The HONO/NO2 ratio has been widely used in many studies as a measure of the degree of heterogeneous conversion of NO2 to HONO [39,41,47,57]. In this study, it was found that the HONO/NO2 ratio (Figure 2c,d) showed an increasing trend in these five years, and the HONO/NO2 ratios at the PD site and the QP site in 2021 were significantly higher than those in the previous four years, which is consistent with the interannual variation of HONO concentrations. The HONO/NO2 ratio showed a decreasing trend in early 2020, likely due to reduced anthropogenic emissions and specific meteorological conditions during the epidemic. In terms of seasonal variations, the HONO/NO2 ratios were significantly higher in summer than in other seasons for both PD and QP, probably because the NO2 photoenhanced heterogeneous phase rreaction was more active in summer. Meanwhile, the lower summer HONO/NO2 ratios in PD 2018 and QP 2019 were due to the presence of missing data in summer. The mean values of 0.047 ± 0.027 and 0.060 ± 0.067 for PD and QP, respectively, were consistent with the range of 0.033–0.134 reported in previous field observations [47,58,59].
The two sites, PD and QP, exhibited a relatively consistent and typical pattern of daily changes in HONO (Figure 3). The concentration of HONO increased rapidly and reached a peak in the morning, with the peak occurring at 8 or 9 a.m., which may be due to emissions from motor vehicles during the morning rush hour. Concentrations then began to decrease, reaching a nadir in the afternoon due to photolysis of HONO, before accumulating during the night. Mean HONO values up to 0.5–2.3 ppb (PD) and 0.4–2.5 ppb (QP) were observed during the daytime, suggesting high daytime HONO production. The nighttime accumulation indicates that HONO production exceeds sinks. Photoresponse has been observed to be a contributing factor to the rise in HONO production levels during the day, resulting in a diurnal pattern of HONO at both sites. These phenomena are consistent with those observed at rural, suburban, and urban sites in other regions [60,61,62]. The period between 2017 and 2021 saw reduced fluctuations in HONO at the PD site, with a more even trend overall. In contrast, the QP site exhibited larger fluctuations. The PD site is predominantly urban, characterized by a paucity of controlled emission sources, leading to more stable changes in HONO concentrations. In contrast, the QP site may be influenced by a more diverse array of sources, including traffic emissions, industrial pollution, and rural activities. The presence of a higher number of diesel and petrol vehicles at the QP site location suggests that traffic emissions directly release NOx and NO2, and generate HONO through nighttime chemical reactions. Geographically, the Qingpu district, where the QP site is located, borders Suzhou and Jiaxing. The impact of pollutants on HONO concentrations may be influenced by regional transport processes.
The variation of HONO with temperature for different years exhibited a typical pattern at the two observation sites (Figure 4). Specifically, the HONO concentrations of PD and QP show a tendency to increase first with increasing temperature. A similar trend was observed in the HONO/NO2 ratio (Figures S1 and S2). However, at temperatures below 20 °C, an increase in HONO concentration was observed with rising temperature, while at temperatures above 20 °C, the effect of temperature on HONO concentration was found to be minimal. This suggests that the effect of temperature on HONO may have an optimal temperature of around 20 °C, which is consistent with previous studies [18,63,64].
As demonstrated in Figure 5, humidity (RH) exerts a substantial influence on the concentration of HONO, with a general trend of increasing HONO concentration with increasing humidity, particularly at high humidity levels (≥85%), where the chemical reaction on the wetted surface promotes the conversion of NO2 to HONO. Cui et al. [47] found that, when the relative humidity is between 40% and 75%, the effect of water on the heterogeneous conversion of NO2 to HONO is stronger than the effect of HONO deposition, thus increasing the conversion efficiency and the accumulation of HONO. Hu et al. [39] found that the effect of relative humidity on HONO can be divided into two parts. When the relative humidity was below 77.96% in autumn and 91.99% in winter, the relative humidity promoted the increase in HONO/NO2, which was consistent with the reaction kinetics of the reaction. The HONO concentration at the PD site varied more steadily and was less affected by humidity, indicating that it had a relatively single source of contamination and a better treatment effect. Conversely, the fluctuation range of HONO concentration at the QP site exhibited a significantly larger variation than that observed at PD site, particularly under conditions of high humidity. This phenomenon may be attributed to the influence of diversified pollution sources (e.g., industrial, traffic, and agricultural emissions) as well as regional pollution transport in the region. It is noteworthy that the HONO concentrations at the QP site exhibited a marked increase under high humidity conditions during the years 2020 and 2021, suggesting a potential enhancement of source-specific activities (e.g., agricultural or industrial emission).

3.2. The Impact of Meteorological Factors on HONO Concentration

The Spearman correlation analysis (Figure S3) reveals the complex interplay between HONO and meteorological variables (T, P, RH, WS, WD) across two distinct environmental settings in Shanghai. Overall, HONO concentrations at both sites exhibit a significant positive correlation with relative humidity (RH) and a negative correlation with wind speed (WS), while the relationships with temperature (T) show regional divergence.
As shown in Figure S3, HONO exhibits different relationships with various parameters, which further our understanding of its generation mechanism and sink. For both PD and QP, there is a significant positive correlation between HONO and relative humidity (RH) (r = 0.38, 0.30). This is consistent with the consensus that the heterogeneous transformation of NO2 on wet surfaces is the main source of HONO at night [33]. High relative humidity is conducive to the formation of water films on the surface and aerosol, thereby promoting the disproportionation or reduction reaction of NO2. As densely populated financial and residential centers, PD is characterized by high NOx emissions from vehicle traffic and a large surface area provided by urban canopies (buildings and paved roads). The positive correlation with RH indicates that the heterogeneous transformation of NO2 on these urban surfaces is the main source [65]. QP areas are usually located near large bodies of water and have high ambient RH. High humidity not only promotes the hydrolysis of NO2 at the surface but also increases the liquid water content (LWC) of aerosol, thus providing more reaction sites for the formation of heterogeneous HONO on particulate surfaces [35]. The observed correlations with RH and wind speed further support the importance of heterogeneous formation pathways, although minor contributions from gas-phase reactions and other sources cannot be completely excluded.
The negative correlation between PD and WS reflects that low wind speeds may trap primary emissions and promote the accumulation of HONO within a stable nighttime boundary layer [66]. The weak correlation between T and HONO (r = −0.016) suggests that the effects of temperature may be the result of competing physical and chemical processes. While higher temperatures can accelerate the chemical kinetics of heterogeneous NO2 to HONO conversion, they are often accompanied by enhanced vertical mixing and boundary layer deepening, thus promoting the dilution of surface pollutants. The near-zero correlation suggests that these mutually offsetting effects cancel each other out in the complex urban environment of PD. This may be attributed to the urban heat island effect, which affects the boundary layer height and thus the dilution volume of HONO emitted from the surface [53].
Unlike traffic-dominated PD, QP is typically located downwind of the urban plume. As shown in Figure S3, the relationship between HONO concentration and P (r = −0.23) and WS (r = −0.31) in QP indicates that HONO concentration is highly sensitive to regional air mass stagnation. In high-pressure systems, NOx transport from the urban core combined with local high humidity environments leads to significant secondary HONO generation [67]. The correlation between HONO and T in QP is more pronounced than in PD (r = 0.21), showing a positive correlation, which may reflect the effects of soil emissions or dew evaporation. As morning temperatures rise, dew evaporation can release captured nitrite back into the gas phase in the form of HONO [68]. The difference between PD and QP suggests that although the chemical formation of HONO (driven by relative humidity and precursors) is universal, the physical environment determines the extent of these effects. In PD, correlation analysis highlights the importance of primary emission accumulation and urban surface reaction. The high density of vertical surfaces in the urban core provides a continuous reactor for NO2 conversion [33]. In QP, analysis shows that secondary generation is enhanced by natural humidity. Suburban landscapes have more lush vegetation and higher regional aerosol loads.
To further identify the pollution source areas, we conducted wind rose diagram analysis at two sites, PD and QP (Figure 6 and Figure S4). The distribution of HONO concentrations with wind direction and speed reveals different local emission characteristics at the two sites.
At the PD site, influenced by industrial port clusters and urban traffic, as shown in Figure 6, the prevailing wind directions during the observation period were primarily east (E) and east–northeast (ENE). When the wind direction was easterly, this direction aligned with the Waigaoqiao industrial area and Shanghai Port, both significant sources of NOx emissions from heavy-duty diesel engines and shipping activities [69]. Notably, the highest frequency peaks were concentrated in low-wind-speed (<2 m/s) areas, indicating that the sampling points were heavily influenced by near-field traffic emissions from the surrounding dense urban road network. In the urban core area, the atmospheric lifetime of HONO is short (typically < 20 min during the day), suggesting that these emission sources are likely located within a 2–5 km radius of the PD site [69].
For the QP site, the wind rose diagram (Figure S4) shows that the main airflow originates from the southeast (SE) and east–southeast (ESE). The southeast winds are particularly noteworthy. Given that downtown Shanghai (including PD and Huangpu districts) lies southeast of QP, this pattern suggests the presence of urban plume transport. While HONO itself may undergo photolysis during transport, its precursor NO2 is transported from the high-emission urban core to the QP suburbs, where it undergoes heterogeneous transformation on local vegetation and moist aerosol particle surfaces. At moderate wind speeds (2–4 m/s), the high-frequency region extends southeastward, indicating that medium-distance NOx transport (10–30 km) is more significant in QP than in PD. Proximity to Dianshan Lake and the resulting higher humidity in the southeasterly airflow further promote secondary HONO generation along this transport path.
However, given the extremely short atmospheric lifetime of HONO, typically only 10 to 20 min under midday photolysis conditions [70], the observed HONO is likely formed locally by transported precursors rather than being transported directly over long distances as HONO. This explains why we focus on local chemical mechanisms rather than large-scale trajectory analysis, as the chemical signal of HONO decays rapidly during air mass transport [71,72]. Therefore, controlling local emissions and understanding the transformation of NO2 in the urban canopy are priorities for AOC emission reduction.
It is worth noting that the significant increase in the frequency of low north–south (N) wind speeds (≤1 m/s) in the PD wind rose diagram in 2021 is a phenomenon worthy of discussion (Figure 6). In 2021, Shanghai was frequently controlled by altered high pressure or weak pressure fields, resulting in stable atmospheric stratification and insufficient power for cold air from the north to move southward. This led to the formation of stagnant weak northerly winds in Pudong, which was conducive to the static accumulation of pollutants [73,74]. As a high-density urban core area, the newly added high-rise buildings or urban renewal north of the observation point increased the surface roughness, and the resulting building shielding effect significantly weakened the background wind speed, transforming medium and high wind speeds into low-speed eddies [75,76]. Considering the background of La Niña, climate anomalies may enhance the local urban heat island circulation. When the background wind is weak, this local thermal circulation leads to an increase in the frequency of winds in specific directions (such as north), but manifests as extremely low wind speeds [73,77].

3.3. HONO Impacts on Atmospheric Oxidation Capacity

Photolysis of HONO is recognized as an important pathway for the formation of OH radical in the atmosphere [78]. In addition, OH radicals are involved in chemical and photochemical processes to form O3 and other secondary pollutants [79]. Therefore, the effect of HONO on OH chemical properties was explored by F0AM modeling. The episodes information selected for this study can be found in Table S3. Diurnal profiles of model-simulated OH chemical budgets with or without constraint on HONO are illustrated in Figure 7 and Figures S5–S7. The average POH produced by HONO photolysis was 1.9 ppb h−1, followed by O3 photolysis (1.5 ppb h−1 ) and ozonolysis of unsaturated VOCs (0.3 ppb h−1) in PD summer, respectively. As shown in Figure 7, total POH decreases significantly in the absence of observed HONO concentration constraints. This is primarily due to the significant reduction in POH by HONO photolysis in the absence of observed HONO, especially in the morning. The rate of OH production is smaller in winter compared to summer, and HONO photolysis plays an important role in winter OH production. From an interannual perspective, there is no significant change in the production of OH. This indicates that ambient HONO is important for accurate analysis of OH atmospheric chemistry. Previous studies have consistently shown that HONO plays a key role in the generation of OH radicals, a key player in atmospheric chemistry. HONO photolysis contributes significantly to the generation of OH radical, with estimates that it can account for up to 60% of daytime OH radical formation, especially in urban environments [32,80]. This process is essential for the oxidation of volatile organic compounds (VOCs) and the generation of secondary pollutants such as ozone. These results are further supported by the study of Ren et al., who showed that HONO photolysis can contribute more than half of the total HOx (OH and HO2) radical generation in urban environments [81]. Zhou et al. and Gil et al. also highlighted the importance of HONO, noting that its role in OH radical generation is crucial for the oxidation of various atmospheric pollutants, significantly affecting air quality [32,39,80].
Figure 8 and Figures S8–S10 depict O3 generation and removal pathways. The HO2 + NO reaction is the main pathway for O3 production. The reaction rate of HO2 + NO was significantly higher in summer (5.9 ppb h−1). In addition, under HONO constraints, the summer HO2 + NO reaction rates increased by 16% from 5.9 to 6.9 ppb h−1, respectively, suggesting that HONO plays a more important role in the production of O3 during the summer. The second pathway for O3 production is RO2 + NO. In summer, the reaction rate of RO2 + NO is 2.9 ppb h−1. Under the constraint of HONO, the reaction rate of RO2 + NO increases to 3.5 ppb h−1, which is a 20% increase, which also indicates that HONO plays a more important role in the production of O3 in summer.
In both periods, the dominant modes of daytime O3 loss were OH + NO2 and RO2 + NO2. The reaction rate of OH + NO2 in summer was 1.4 ppb h−1. Under HONO constraints, the reaction rate in summer increased by 21% to 1.7 ppb h−1, which suggests that HONO plays a more important role in summer O3 loss as well. The summer RO2 + NO2 reaction rate was 0.67 ppb h−1, and under HONO constraints, the RO2 + NO2 reaction rate increased by 19% to 0.8 ppb h−1, respectively, which also suggests that HONO plays a more important role in summer O3 loss. The third pathway for daytime O3 loss is O3 photolysis. The rates of daytime O3 photolysis in summer and winter with HONO limitation were the same as without HONO limitation. These phenomena suggest that HONO increases the O3 loss rate mainly through the OH + NO2 reaction, and to a lesser extent the RO2 + NO2 reaction which had no effect on the O3 photolysis reaction.
To investigate the effect of HONO on O3 sensitivity, we used RIRO3 to reflect the relative changes in O3 production rates with changing precursor mixing ratios [82]. The results show that RIRO3 is subject to significant seasonal and annual variations in both regions, with winter conditions being particularly conducive to O3 formation (Figure S11). Specifically, both PD and QP had lower O3 sensitivities during the summer months of each year, with significant variations between years. In contrast, the RIRO3 was significantly higher in winter than in summer for both PD and QP, suggesting that winter O3 formation is more sensitive to HONO. Recent studies have indeed demonstrated this trend. For example, Wang et al. (2021) highlighted that O3 concentrations tend to peak in winter due to different photochemical mechanisms, with the contribution of HONO as a precursor enhanced under colder conditions [83]. In a related study, Zhang et al. pointed out that the amplification effect of HONO and its contribution to O3 formation becomes particularly important in winter, because the reduced photolysis rate of other precursors limits the production of O3 through other pathways [84]. In addition, Johnson et al. investigated seasonal trends and showed that winter O3 levels are more sensitive to changes in precursors, such as changes in NOx and HONO concentrations [85]. These studies and the present study together suggest that the increased sensitivity to HONO in winter can significantly affect ozone formation, especially in heavily polluted urban areas such as PD and QP in Shanghai.
In summer, the RIRO3 of PD is relatively higher than that of QP in 2019 and 2021, but the RIRO3 of QP is relatively more stable, suggesting that HONO has a greater impact on the more urbanised PD, probably due to the presence of higher concentrations and greater reactivity of HONO in highly polluted environments, which further contributes to the production of O3. Several studies have shown that HONO contributes more to O3 production in polluted urban areas due to complex interactions between NOx and VOC emissions. For example, studies conducted during severe pollution events in China showed that HONO’s contribution to O3 is more pronounced in urban areas, where atmospheric chemistry is heavily influenced by human activities. Modeling studies have also shown that areas with higher HONO concentrations, such as cities like Beijing, have a greater impact on O3 levels than rural or less polluted areas [30,32,86]. These findings highlight the important role of HONO in enhancing atmospheric reactivity in urbanized environments such as PD, leading to elevated O3 levels during pollution events. In 2020, the RIRO3 of both regions shows a decreasing trend, indicating a lower contribution of HONO to O3 production in this year, which may be related to meteorological conditions or pollutant control measures. The factors represented in these areas are moderately sensitive to O3, but this variation suggests the influence of local conditions or meteorological factors during the summer [87].
O3 sensitivity is generally higher in winter than in summer for both PD and QP. The higher contribution of HONO to O3 production in winter may be due to the weaker sunlight intensity in winter, the lower contribution of other O3 precursors (e.g., NOx and VOCs) to O3 production, and the ability of HONO to continue to contribute to O3 production because it still produces OH under low light conditions [88,89,90]. The static winter weather may also lead to the accumulation of pollutants, increasing the reaction time of HONO in the atmosphere and further increasing the rate of O3 production [32,91]. The RIRO3 of QP is higher than that of PD in 2018 and 2020, which may be due to the fact that QP, as a suburb, is more affected by the long-range transport of HONO and other pollutants, resulting in the O3 production being more sensitive to HONO [92,93,94]. The RIRO3 of PD is slightly higher than that of QP in 2019 and 2021, and the margin of error is larger in 2021, suggesting that the influence of HONO is more variable in PD. It is possible that more sources of pollution in the urban area, as well as complex meteorological conditions and chemical processes, make the sensitivity of HONO to O3 more uncertain.

4. Conclusions

This study investigated the characteristics of HONO in the atmosphere of urban (PD) and suburban (QP) areas of Shanghai and its role in atmospheric oxidation capacity. By combining observational analysis and meteorological interpretation, this study provides new insights into the formation mechanism of HONO and its environmental impact in Shanghai.
The results show that although primary nitrogen oxide (NOx) emissions have significantly decreased due to the “Blue Sky Protection Campaign” and periodic social restrictions (such as the COVID-19 lockdowns in 2020), HONO concentrations still exhibit high persistence, with average concentrations ranging from 0.74 ± 0.45 ppb to 1.38 ± 0.52 ppb from 2017 to 2021. HONO concentrations at both sites showed a consistent seasonal variation pattern, with higher concentrations in summer and a distinct morning peak (8–9 a.m.), mainly influenced by vehicle exhaust emissions and light-induced heterogeneous reactions. Compared to the PD site in the urban area, the QP site in the suburbs had generally higher HONO concentrations and greater fluctuations, which may be influenced by multiple local sources and regional transport. The spatial differences between the two regions highlight the complexity of HONO sources. PD is primarily influenced by traffic emissions and heterogeneous reactions over dense urban canopies, while QP is more susceptible to urban plume transport, and higher regional humidity promotes secondary formation.
Comprehensive analysis of meteorological factors and chemical precursors indicates that HONO is not only a byproduct of pollution but also a sensitive indicator of atmospheric stability and surface chemistry. A significant positive correlation exists between HONO and RH at both sites (r = 0.38, 0.30). High relative humidity (≥85%) significantly promotes the heterogeneous conversion of NO2 to HONO, especially at the QP site. This confirms that the heterogeneous conversion of NO2 on moist surfaces remains a major source of HONO. HONO concentrations are also closely related to temperature. The optimal temperature for HONO accumulation is approximately 20 °C. Furthermore, wind rose analysis identifies specific localized areas, such as the industrial port cluster east of PD and the urban traffic corridor southeast of QP. Notably, the frequent occurrence of low-speed calm winds observed in 2021 indicates that physical diffusion constraints significantly exacerbate HONO accumulation, independent of short-term emission fluctuations. Meteorological conditions have a significant controlling effect on HONO concentrations. Weak winds and stable atmospheric stratification favor pollutant accumulation and enhance heterogeneous transformation processes, while wind direction changes reflect the influence of local emission sources.
The most significant aspect of this study is the quantification of the role of HONO in driving atmospheric oxidative capacity (AOC). We found that the photolysis of HONO is the primary driver of hydroxyl radical (OH) generation, particularly in summer with an average generation of 1.9 ppb h−1. This surge in radical accelerates the oxidation of VOCs, subsequently forming near-surface O3. Under HONO constraints, the rates of O3 generation via the HO2 + NO and RO2 + NO pathways significantly increased by 16% and 20%, respectively. O3 generation was more sensitive to HONO in winter than in summer, highlighting the crucial role of HONO in maintaining atmospheric reactivity during periods of low solar radiation. This study indicates that HONO can significantly enhance atmospheric oxidation through its rapid photolysis, thereby promoting the formation of secondary pollutants such as ozone and secondary aerosol. This underscores the necessity of explicitly considering HONO chemical processes in air quality models to improve the accuracy of photochemical pollution prediction.
This research has significant implications for air pollution control strategies in the Yangtze River Delta. Effective mitigation of photochemical pollution should not only focus on traditional pollutant precursors (such as NOx and VOCs) but also consider various processes controlling HONO formation, especially heterogeneous reactions occurring under high humidity and stagnant meteorological conditions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/atmos17060558/s1, Text S1: Quality Assurance and Quality Control (QA/QC); Text S2: Estimation of particulate matter surface area concentration [95,96,97,98]; Text S3: HONO Source and Sink Budget Analysis [99,100,101,102]; Figure S1: Interannual variation of HONO/NO2 with temperature in PD; Figure S2: Interannual variation of HONO/NO2 with temperature in QP; Figure S3: Spearman correlation analysis of HONO concentration with temperature (T), relative humidity (RH), wind speed (WS), wind direction (WD), and atmospheric pressure (P) at the PD and QP sites; Figure S4: 2017–2021 wind rose analysis in QP site. Color represents wind speed, radius represents frequency, and angle represents wind direction; Figure S5: Diurnal profiles of model-simulated OH chemical budgets with or without constraint on HONO in PD winter; Figure S6: Diurnal profiles of model-simulated OH chemical budgets with or without constraint on HONO in QP summer; Figure S7: Diurnal profiles of model-simulated OH chemical budgets with or without constraint on HONO in QP winter; Figure S8: Diurnal profiles of model-simulated O3 chemical budgets with or without constraint on HONO in PD winter. Other RO2 + NO stands for RO2 + NO reactions other than CH3O2 + NO; Figure S9: Diurnal profiles of model-simulated O3 chemical budgets with or without constraint on HONO in QP summer. Other RO2 + NO stands for RO2 + NO reactions other than CH3O2 + NO; Figure S10: Diurnal profiles of model-simulated O3 chemical budgets with or without constraint on HONO in QP winter. Other RO2 + NO stands for RO2 + NO reactions other than CH3O2 + NO; Figure S11: RIR of O3 in Pudong (PD: Green) and Qingpu (QP: Blue) of Shanghai during summer (a) and winter (b) 2018–2021; Table S1: Ranges of key parameters used in sensitivity analyses [103,104,105,106]; Table S2: Updated HONO formation mechanisms in F0AM; Table S3: Mean values of PM2.5 and HONO for the episodes selected in this study.

Author Contributions

Conceptualization and design, S.W.; Research methods, S.W. and M.H.; Data analysis, W.Z. and S.W.; Fieldwork, S.W. and W.Z.; Resource support, M.H. and Q.F.; Data organization: M.H.; Writing—Drafting: W.Z.; Writing—Review and Editing: S.W. and W.Z.; Supervision: S.W.; Funding acquisition: J.F. and S.W. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by National Natural Science Foundation of China (No. 22206119) and National Key Research and Development Program of China (No. 2022YFC3703500).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

To request the data files, please contact the corresponding author via email. These files are intended for research purposes only.

Acknowledgments

I sincerely thank the Shanghai Environmental Monitoring Center and the Shanghai Academy of Environmental Sciences for providing data.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
HONONitrous acid
AOCAtmospheric oxidation capacity
PDPudong
QPQingpu
RNSReactive nitrogen species
NOXNitrogen oxides
VOCsVolatile organic compounds
YRDYangtze River Delta
F0AMFramework for 0-D Atmospheric Modelling
MCMMaster Chemistry Mechanism
PBLPlanetary boundary layer
RHRelative humidity
UVUltraviolet
FIDFlame ionization detector
MSMass spectrometry
RIRRelative Incremental Reactivity

References

  1. Chan, K.L.; Wang, S.; Liu, C.; Zhou, B.; Wenig, M.O.; Saiz-Lopez, A. On the summertime air quality and related photochemical processes in the megacity Shanghai, China. Sci. Total Environ. 2017, 580, 974–983. [Google Scholar] [CrossRef]
  2. Liu, Y.; Zhang, Y.; Chaofan, L.; Yan, C.; Feng, Z.; Zheng, F.; Fan, X.; Chen, Y.; Wang, W.; Chu, B.; et al. The promotion effect of nitrous acid on aerosol formation in wintertime in Beijing: The possible contribution of traffic-related emissions. Atmos. Chem. Phys. 2020, 20, 13023–13040. [Google Scholar] [CrossRef]
  3. Su, H.; Cheng, Y.F.; Shao, M.; Gao, D.F.; Yu, Z.Y.; Zeng, L.M.; Slanina, J.; Zhang, Y.H.; Wiedensohler, A. Nitrous acid (HONO) and its daytime sources at a rural site during the 2004 PRIDE-PRD experiment in China. J. Geophys. Res. Atmos. 2008, 113, D14312. [Google Scholar] [CrossRef]
  4. Sarwar, G.; Roselle, S.J.; Mathur, R.; Appel, W.; Dennis, R.L.; Vogel, B. A comparison of CMAQ HONO predictions with observations from the Northeast Oxidant and Particle Study. Atmos. Environ. 2008, 42, 5760–5770. [Google Scholar] [CrossRef]
  5. Romanias, M.N.; El Zein, A.; Bedjanian, Y. Reactive uptake of HONO on aluminium oxide surface. J. Photochem. Photobiol. A Chem. 2012, 250, 50–57. [Google Scholar] [CrossRef]
  6. El Zein, A.; Bedjanian, Y. Reactive Uptake of HONO to TiO2 Surface: “Dark” Reaction. J. Phys. Chem. A 2012, 116, 3665–3672. [Google Scholar] [CrossRef]
  7. Li, X.; Brauers, T.; Häseler, R.; Bohn, B.; Fuchs, H.; Hofzumahaus, A.; Holland, F.; Lou, S.; Lu, K.D.; Rohrer, F.; et al. Exploring the atmospheric chemistry of nitrous acid (HONO) at a rural site in Southern China. Atmos. Chem. Phys. 2012, 12, 1497–1513. [Google Scholar] [CrossRef]
  8. Stemmler, K.; Ndour, M.; Elshorbany, Y.; Kleffmann, J.; D’Anna, B.; George, C.; Bohn, B.; Ammann, M. Light induced conversion of nitrogen dioxide into nitrous acid on submicron humic acid aerosol. Atmos. Chem. Phys. 2007, 2007, 4237. [Google Scholar] [CrossRef]
  9. Ndour, M.; D’Anna, B.; George, C.; Ka, O.; Balkanski, Y.; Kleffmann, J.; Stemmler, K.; Ammann, M. Photoenhanced uptake of NO2 on mineral dust: Laboratory experiments and model simulations. Geophys. Res. Lett. 2008, 35, L05812. [Google Scholar] [CrossRef]
  10. Xia, H.; Huang, D.; Bao, F.; Li, M.; Zhang, Y.; Chen, C.; Zhao, J. Photochemical aging of Beijing urban PM2.5: Production of oxygenated volatile organic compounds. Sci. Total Environ. 2020, 743, 140751. [Google Scholar] [CrossRef] [PubMed]
  11. Ye, C.; Gao, H.; Zhang, N.; Zhou, X. Photolysis of Nitric Acid and Nitrate on Natural and Artificial Surfaces. Environ. Sci. Technol. 2016, 50, 3530–3536. [Google Scholar] [CrossRef]
  12. Ye, C.; Zhang, N.; Gao, H.; Zhou, X. Photolysis of Particulate Nitrate as a Source of HONO and NOx. Environ. Sci. Technol. 2017, 51, 6849–6856. [Google Scholar] [CrossRef]
  13. Li, B.; Gao, J.; Chen, C.; Wen, L.; Zhang, Y.; Li, J.; Zhang, Y.; Du, X.; Zhang, K.; Wang, J. Exploring HONO production from particulate nitrate photolysis in representative regions of China: Characteristics, influencing factors, and environmental implications. Atmos. Chem. Phys. 2024, 24, 13183–13198. [Google Scholar] [CrossRef]
  14. Romer, P.S.; Wooldridge, P.J.; Crounse, J.D.; Kim, M.J.; Wennberg, P.O.; Dibb, J.E.; Scheuer, E.; Blake, D.R.; Meinardi, S.; Brosius, A.L.; et al. Constraints on Aerosol Nitrate Photolysis as a Potential Source of HONO and NOx. Environ. Sci. Technol. 2018, 52, 13738–13746. [Google Scholar] [CrossRef] [PubMed]
  15. Andersen, S.T.; Carpenter, L.J.; Reed, C.; Lee, J.D.; Chance, R.; Sherwen, T.; Vaughan, A.R.; Stewart, J.; Edwards, P.M.; Bloss, W.J.; et al. Extensive field evidence for the release of HONO from the photolysis of nitrate aerosols. Sci. Adv. 2023, 9, eadd6266. [Google Scholar] [CrossRef] [PubMed]
  16. Pitts, J.N., Jr.; Sanhueza, E.; Atkinson, R.; Carter, W.P.L.; Winer, A.M.; Harris, G.W.; Plum, C.N. An investigation of the dark formation of nitrous acid in environmental chambers. Int. J. Chem. Kinet. 1984, 16, 919–939. [Google Scholar] [CrossRef]
  17. Chen, D.; Zhou, L.; Wang, W.; Lian, C.; Liu, H.; Luo, L.; Xiao, K.; Chen, Y.; Song, D.; Tan, Q.; et al. Integrating Chemical Mechanisms and Feature Engineering in Machine Learning Models: A Novel Approach to Analyzing HONO Budget. Environ. Sci. Technol. 2024, 58, 22267–22277. [Google Scholar] [CrossRef] [PubMed]
  18. Zhang, W.; Tong, S.; Lin, D.; Li, F.; Zhang, X.; Wang, L.; Ji, D.; Tang, G.; Liu, Z.; Hu, B.; et al. Atmospheric chemistry of nitrous acid and its effects on hydroxyl radical and ozone at the urban area of Beijing in early spring 2021. Environ. Pollut. 2023, 316, 120710. [Google Scholar] [CrossRef]
  19. Elshorbany, Y.F.; Kurtenbach, R.; Wiesen, P.; Lissi, E.; Rubio, M.; Villena, G.; Gramsch, E.; Rickard, A.R.; Pilling, M.J.; Kleffmann, J. Oxidation capacity of the city air of Santiago, Chile. Atmos. Chem. Phys. 2009, 9, 2257–2273. [Google Scholar] [CrossRef]
  20. Lu, K.; Rohrer, F.; Holland, F.; Fuchs, H.; Bohn, B.; Brauers, T.; Chang, C.-C.; Häseler, M.; Hu, M.; Kita, K.; et al. Observation and modelling of OH and HO2 concentrations in the Pearl River Delta 2006: A missing OH source in a VOC rich atmosphere. Atmos. Chem. Phys. 2012, 2012, 1541–1569. [Google Scholar] [CrossRef]
  21. Stutz, J.; Kim, E.S.; Platt, U.; Bruno, P.; Perrino, C.; Febo, A. UV-visible absorption cross sections of nitrous acid. J. Geophys. Res. Atmos. 2000, 105, 14585–14592. [Google Scholar] [CrossRef]
  22. Stone, D.; Whalley, L.K.; Heard, D.E. Tropospheric OH and HO2 radicals: Field measurements and model comparisons. Chem. Soc. Rev. 2012, 41, 6348–6404. [Google Scholar] [CrossRef] [PubMed]
  23. Seinfeld, J.H.; Pandis, S.N.; Noone, K.J. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. Phys. Today 1998, 51, 88–90. [Google Scholar] [CrossRef]
  24. Gu, R.; Zheng, P.; Chen, T.; Dong, C.; Wang, Y.n.; Liu, Y.; Liu, Y.; Luo, Y.; Han, G.; Wang, X.; et al. Atmospheric nitrous acid (HONO) at a rural coastal site in North China: Seasonal variations and effects of biomass burning. Atmos. Environ. 2020, 229, 117429. [Google Scholar] [CrossRef]
  25. Alicke, B.; Geyer, A.; Hofzumahaus, A.; Holland, F.; Konrad, S.; Pätz, H.W.; Schäfer, J.; Stutz, J.; Volz-Thomas, A.; Platt, U. OH formation by HONO photolysis during the BERLIOZ experiment. J. Geophys. Res. Atmos. 2003, 108, PHO 3-1–PHO 3-17. [Google Scholar] [CrossRef]
  26. Elshorbany, Y.F.; Kleffmann, J.; Kurtenbach, R.; Lissi, E.; Rubio, M.; Villena, G.; Gramsch, E.; Rickard, A.R.; Pilling, M.J.; Wiesen, P. Seasonal dependence of the oxidation capacity of the city of Santiago de Chile. Atmos. Environ. 2010, 44, 5383–5394. [Google Scholar] [CrossRef]
  27. Sillman, S. The use of NO, H2O2, and HNO3 as indicators for ozone-NOx -hydrocarbon sensitivity in urban locations. J. Geophys. Res. Atmos. 1995, 100, 14175–14188. [Google Scholar] [CrossRef]
  28. Atkinson, R. Atmospheric chemistry of VOCs and NOx. Atmos. Environ. 2000, 34, 2063–2101. [Google Scholar] [CrossRef]
  29. Liu, P.; Xue, C.; Ye, C.; Liu, C.; Zhang, C.; Wang, J.; Zhang, Y.; Liu, J.; Mu, Y. The Lack of HONO Measurement May Affect the Accurate Diagnosis of Ozone Production Sensitivity. ACS Environ. Au 2023, 3, 18–23. [Google Scholar] [CrossRef]
  30. Ye, C.; Lu, K.; Ma, X.; Qiu, W.; Li, S.; Yang, X.; Xue, C.; Zhai, T.; Liu, Y.; Li, X.; et al. HONO chemistry at a suburban site during the EXPLORE-YRD campaign in 2018: Formation mechanisms and impacts on O3 production. Atmos. Chem. Phys. 2023, 23, 15455–15472. [Google Scholar] [CrossRef]
  31. Zhang, R.; Sarwar, G.; Fung, J.C.H.; Lau, A.K.H.; Zhang, Y. Examining the Impact of Nitrous Acid Chemistry on Ozone and PM over the Pearl River Delta Region. Adv. Meteorol. 2012, 2012, 140932. [Google Scholar] [CrossRef]
  32. Fu, X.; Wang, T.; Zhang, L.; Li, Q.; Wang, Z.; Xia, M.; Yun, H.; Wang, W.; Yu, C.; Yue, D.; et al. The significant contribution of HONO to secondary pollutants during a severe winter pollution event in southern China. Atmos. Chem. Phys. 2019, 19, 1–14. [Google Scholar] [CrossRef]
  33. Kleffmann, J. Daytime Sources of Nitrous Acid (HONO) in the Atmospheric Boundary Layer. ChemPhysChem 2007, 8, 1137–1144. [Google Scholar] [CrossRef]
  34. Zhang, W.; Tong, S.; Ge, M.; An, J.; Shi, Z.; Hou, S.; Xia, K.; Qu, Y.; Zhang, H.; Chu, B.; et al. Variations and sources of nitrous acid (HONO) during a severe pollution episode in Beijing in winter 2016. Sci. Total Environ. 2019, 648, 253–262. [Google Scholar] [CrossRef]
  35. Bernard, F.; Cazaunau, M.; Grosselin, B.; Zhou, B.; Zheng, J.; Liang, P.; Zhang, Y.; Ye, X.; Daële, V.; Mu, Y.; et al. Measurements of nitrous acid (HONO) in urban area of Shanghai, China. Environ. Sci. Pollut. Res. 2016, 23, 5818–5829. [Google Scholar] [CrossRef]
  36. Feng, T.; Zhao, S.; Liu, L.; Long, X.; Gao, C.; Wu, N. Nitrous acid emission from soil bacteria and related environmental effect over the North China Plain. Chemosphere 2022, 287, 132034. [Google Scholar] [CrossRef]
  37. Zhang, L.; Li, Q.; Wang, T.; Ahmadov, R.; Zhang, Q.; Li, M.; Lv, M. Combined impacts of nitrous acid and nitryl chloride on lower-tropospheric ozone: New module development in WRF-Chem and application to China. Atmos. Chem. Phys. 2017, 17, 9733–9750. [Google Scholar] [CrossRef]
  38. Ge, Y.; Shi, X.; Ma, Y.; Zhang, W.; Ren, X.; Zheng, J.; Zhang, Y. Seasonality of nitrous acid near an industry zone in the Yangtze River Delta region of China: Formation mechanisms and contribution to the atmospheric oxidation capacity. Atmos. Environ. 2021, 254, 118420. [Google Scholar] [CrossRef]
  39. Hu, B.; Duan, J.; Hong, Y.; Xu, L.; Li, M.; Bian, Y.; Qin, M.; Fang, W.; Xie, P.; Chen, J. Exploration of the atmospheric chemistry of nitrous acid in a coastal city of southeastern China: Results from measurements across four seasons. Atmos. Chem. Phys. 2022, 22, 371–393. [Google Scholar] [CrossRef]
  40. Ni, X.; Sun, C.; Zhang, Y.; Liang, B.; Zhou, S.; Lan, G.; Zhao, J. Atmospheric HONO formation during and after the Spring Festival holidays in a coastal city of China. J. Environ. Sci. 2023, 127, 251–263. [Google Scholar] [CrossRef] [PubMed]
  41. Liu, Y.; Nie, W.; Xu, Z.; Wang, T.; Wang, R.; Li, Y.; Wang, L.; Chi, X.; Ding, A. Semi-quantitative understanding of source contribution to nitrous acid (HONO) based on 1 year of continuous observation at the SORPES station in eastern China. Atmos. Chem. Phys. 2019, 19, 13289–13308. [Google Scholar] [CrossRef]
  42. Crilley, L.R.; Kramer, L.J.; Ouyang, B.; Duan, J.; Zhang, W.; Tong, S.; Ge, M.; Tang, K.; Qin, M.; Xie, P.; et al. Intercomparison of nitrous acid (HONO) measurement techniques in a megacity (Beijing). Atmos. Meas. Tech. 2019, 12, 6449–6463. [Google Scholar] [CrossRef]
  43. Heland, J.; Kleffmann, J.; Kurtenbach, R.; Wiesen, P. A New Instrument to Measure Gaseous Nitrous Acid (HONO) in the Atmosphere. Environ. Sci. Technol. 2001, 35, 3207–3212. [Google Scholar] [CrossRef]
  44. Cao, T.; Wang, H.; Li, L.; Lu, X.; Liu, Y.; Fan, S. Fast spreading of surface ozone in both temporal and spatial scale in Pearl River Delta. J. Environ. Sci. 2024, 137, 540–552. [Google Scholar] [CrossRef]
  45. Zhang, J.; Chen, C.; Su, Y.; Guo, W.; Fu, X.; Long, Y.; Peng, X.; Zhang, W.; Huang, X.; Wang, G. Characterization of summertime single aerosol particles in Chengdu (China): Interannual evolution and impact of COVID-19 lockdown. Sci. Total Environ. 2024, 907, 167765. [Google Scholar] [CrossRef] [PubMed]
  46. Feng, J.; Ren, E.; Hu, M.; Fu, Q.; Duan, Y.; Huang, C.; Zhao, Y.; Wang, S. Budget of atmospheric nitrous acid (HONO) during the haze and clean periods in Shanghai: Importance of heterogeneous reactions. Sci. Total Environ. 2023, 900, 165717. [Google Scholar] [CrossRef]
  47. Cui, L.; Li, R.; Zhang, Y.; Meng, Y.; Fu, H.; Chen, J. An observational study of nitrous acid (HONO) in Shanghai, China: The aerosol impact on HONO formation during the haze episodes. Sci. Total Environ. 2018, 630, 1057–1070. [Google Scholar] [CrossRef]
  48. Wolfe, G.M.; Marvin, M.R.; Roberts, S.J.; Travis, K.R.; Liao, J. The Framework for 0-D Atmospheric Modeling (F0AM) v3.1. Geosci. Model Dev. 2016, 9, 3309–3319. [Google Scholar] [CrossRef]
  49. Xue, C. Substantially Growing Interest in the Chemistry of Nitrous Acid (HONO) in China: Current Achievements, Problems, and Future Directions. Environ. Sci. Technol. 2022, 56, 7375–7377. [Google Scholar] [CrossRef]
  50. Yu, C.; Wang, Z.; Xia, M.; Fu, X.; Wang, W.; Jun Tham, Y.; Chen, T.; Zheng, P.; Li, H.; Shan, Y.; et al. Heterogeneous N2O5 reactions on atmospheric aerosols at four Chinese sites: Improving model representation of uptake parameters. Atmos. Chem. Phys. 2020, 20, 4367–4378. [Google Scholar] [CrossRef]
  51. Zang, H.; Zhao, Y.; Huo, J.; Zhao, Q.; Fu, Q.; Duan, Y.; Shao, J.; Huang, C.; An, J.; Xue, L.; et al. High atmospheric oxidation capacity drives wintertime nitrate pollution in the eastern Yangtze River Delta of China. Atmos. Chem. Phys. 2022, 22, 4355–4374. [Google Scholar] [CrossRef]
  52. Rohrer, F.; Berresheim, H. Strong correlation between levels of tropospheric hydroxyl radicals and solar ultraviolet radiation. Nature 2006, 442, 184–187. [Google Scholar] [CrossRef]
  53. Jia, C.; Tong, S.; Zhang, W.; Zhang, X.; Li, W.; Wang, Z.; Wang, L.; Liu, Z.; Hu, B.; Zhao, P.; et al. Pollution characteristics and potential sources of nitrous acid (HONO) in early autumn 2018 of Beijing. Sci. Total Environ. 2020, 735, 139317. [Google Scholar] [CrossRef]
  54. Zhang, X.; Tong, S.; Jia, C.; Zhang, W.; Wang, Z.; Tang, G.; Hu, B.; Liu, Z.; Wang, L.; Zhao, P.; et al. Elucidating HONO formation mechanism and its essential contribution to OH during haze events. npj Clim. Atmos. Sci. 2023, 6, 55. [Google Scholar] [CrossRef]
  55. Liu, J.; Li, B.; Deng, H.; Yang, Y.; Song, W.; Wang, X.; Luo, Y.; Francisco, J.S.S.; Li, L.; Gligorovski, S. Resolving the Formation Mechanism of HONO via Ammonia-Promoted Photosensitized Conversion of Monomeric NO2 on Urban Glass Surfaces. J. Am. Chem. Soc. 2023, 145, 11488–11493. [Google Scholar] [CrossRef] [PubMed]
  56. Gil, J.; Lee, M.; Lee, H.; Jang, J. Seasonal Characteristics of HONO Variations in Seoul during 2021–2022. J. Korean Soc. Atmos. Environ. 2023, 39, 308–319. [Google Scholar] [CrossRef]
  57. Spataro, F.; Ianniello, A.; Esposito, G.; Allegrini, I.; Zhu, T.; Hu, M. Occurrence of atmospheric nitrous acid in the urban area of Beijing (China). Sci. Total Environ. 2013, 447, 210–224. [Google Scholar] [CrossRef]
  58. Stutz, J.; Alicke, B.; Ackermann, R.; Geyer, A.; Wang, S.; White, A.B.; Williams, E.J.; Spicer, C.W.; Fast, J.D. Relative humidity dependence of HONO chemistry in urban areas. J. Geophys. Res. Atmos. 2004, 109, D03307. [Google Scholar] [CrossRef]
  59. Wang, S.; Zhou, R.; Zhao, H.; Wang, Z.; Chen, L.; Zhou, B. Long-term observation of atmospheric nitrous acid (HONO) and its implication to local NO2 levels in Shanghai, China. Atmos. Environ. 2013, 77, 718–724. [Google Scholar] [CrossRef]
  60. Liu, Y.; Ni, S.; Jiang, T.; Xing, S.; Zhang, Y.; Bao, X.; Feng, Z.; Fan, X.; Zhang, L.; Feng, H. Influence of Chinese New Year overlapping COVID-19 lockdown on HONO sources in Shijiazhuang. Sci. Total Environ. 2020, 745, 141025. [Google Scholar] [CrossRef] [PubMed]
  61. Burling, I.; Yokelson, R.; Griffith, D.; Johnson, T.; Veres, P.; Roberts, J.; Warneke, C.; Urbanski, S.; Reardon, J.; Weise, D.; et al. Laboratory measurements of trace gas emissions from biomass burning of fuel types from the Southeastern and Southwestern United States. Atmos. Chem. Phys. Discuss. 2010, 10, 11115–11130. [Google Scholar] [CrossRef]
  62. Shi, X.; Ge, Y.; Zheng, J.; Ma, Y.; Ren, X.; Zhang, Y. Budget of nitrous acid and its impacts on atmospheric oxidative capacity at an urban site in the central Yangtze River Delta region of China. Atmos. Environ. 2020, 238, 117725. [Google Scholar] [CrossRef]
  63. Wen, L.; Chen, T.; Zheng, P.; Wu, L.; Wang, X.; Mellouki, A.; Xue, L.; Wang, W. Nitrous acid in marine boundary layer over eastern Bohai Sea, China: Characteristics, sources, and implications. Sci. Total Environ. 2019, 670, 282–291. [Google Scholar] [CrossRef]
  64. Xing, C.; Xu, S.; Song, Y.; Liu, C.; Liu, Y.; Lu, K.; Tan, W.; Zhang, C.; Hu, Q.; Wang, S.; et al. A new insight into the vertical differences in NO2 heterogeneousreaction to produce HONO over inland and marginal seas. Atmos. Chem. Phys. 2023, 23, 5815–5834. [Google Scholar] [CrossRef]
  65. Gu, R.; Shen, H.; Xue, L.; Wang, T.; Gao, J.; Li, H.; Liang, Y.; Xia, M.; Yu, C.; Liu, Y.; et al. Investigating the sources of atmospheric nitrous acid (HONO) in the megacity of Beijing, China. Sci. Total Environ. 2022, 812, 152270. [Google Scholar] [CrossRef]
  66. Cheng, P.; Ling, J.; Gong, Y.; Yang, W.; Wang, S.; Han, B.; Li, X.; Yuan, B.; Pei, C.; Shen, J.; et al. Understanding Nitrous Acid (HONO) in the Urban Boundary Layer Using Continuous HONO Measurements at a 450 m Tall Tower in Guangzhou, China. Environ. Sci. Technol. 2025, 59, 10411–10421. [Google Scholar] [CrossRef]
  67. Xuan, H.; Liu, J.; Zhao, Y.; Cao, Q.; Chen, T.; Wang, Y.; Liu, Z.; Sun, X.; Li, H.; Zhang, P.; et al. Relative humidity driven nocturnal HONO formation mechanism in autumn haze events of Beijing. npj Clim. Atmos. Sci. 2024, 7, 193. [Google Scholar] [CrossRef]
  68. Wang, L.; Wen, L.; Xu, C.; Chen, J.-M.; Wang, X.; Yang, L.; Wang, W.; Yang, X.; Sui, X.; Yao, L.; et al. HONO and its potential source particulate nitrite at an urban site in North China during the cold season. Sci. Total Environ. 2015, 538, 93–101. [Google Scholar] [CrossRef]
  69. Hao, Q.; Jiang, N.; Zhang, R.; Yang, L.; Li, S. Characteristics, sources, and reactions of nitrous acid during winter at an urban site in the Central Plains Economic Region in China. Atmos. Chem. Phys. 2020, 20, 7087–7102. [Google Scholar] [CrossRef]
  70. Finlayson-Pitts, B.J.; Wingen, L.M.; Sumner, A.L.; Syomin, D.; Ramazan, K.A. The heterogeneous hydrolysis of NO2 in laboratory systems and in outdoor and indoor atmospheres: An integrated mechanism. Phys. Chem. Chem. Phys. 2003, 5, 223–242. [Google Scholar] [CrossRef]
  71. Bloss, W.J.; Kramer, L.; Crilley, L.R.; Vu, T.; Harrison, R.M.; Shi, Z.; Lee, J.D.; Squires, F.A.; Whalley, L.K.; Slater, E.; et al. Insights into air pollution chemistry and sulphate formation from nitrous acid (HONO) measurements during haze events in Beijing. Faraday Discuss. 2021, 226, 223–238. [Google Scholar] [CrossRef]
  72. Zhu, Y.; Wang, Y.; Zhou, X.; Elshorbany, Y.F.; Ye, C.; Hayden, M.; Peters, A.J. An investigation into the chemistry of HONO in the marine boundary layer at Tudor Hill Marine Atmospheric Observatory in Bermuda. Atmos. Chem. Phys. 2022, 22, 6327–6346. [Google Scholar] [CrossRef]
  73. Fan, Y.; Li, Y.; Bejan, A.; Wang, Y.; Yang, X. Horizontal extent of the urban heat dome flow. Sci. Rep. 2017, 7, 11681. [Google Scholar] [CrossRef]
  74. Wang, Q.; Fan, Y.; Hang, J.; Li, Y. Interacting urban heat island circulations as affected by weak background wind. Build. Environ. 2019, 160, 106224. [Google Scholar] [CrossRef]
  75. Sun, Y.; Zhang, N.; Ao, X.; Gao, Y. Numerical Studies on the Influence of Building Morphology on Urban Canopy Wind Speed. J. Adv. Model. Earth Syst. 2024, 16, e2023MS003881. [Google Scholar] [CrossRef]
  76. Theeuwes, N.E.; Ronda, R.J.; Harman, I.N.; Christen, A.; Grimmond, C.S.B. Parametrizing Horizontally-Averaged Wind and Temperature Profiles in the Urban Roughness Sublayer. Bound. Layer Meteorol. 2019, 173, 321–348. [Google Scholar] [CrossRef]
  77. Wang, Q.; Wang, Y.; Fan, Y.; Hang, J.; Li, Y. Urban heat island circulations of an idealized circular city as affected by background wind speed. Build. Environ. 2019, 148, 433–447. [Google Scholar] [CrossRef]
  78. Rohrer, F.; Bohn, B.; Brauers, T.; Brüning, D.; Johnen, F.J.; Wahner, A.; Kleffmann, J. Characterisation of the photolytic HONO-source in the atmosphere simulation chamber SAPHIR. Atmos. Chem. Phys. 2005, 5, 2189–2201. [Google Scholar] [CrossRef]
  79. Anderson, D.C.; Duncan, B.N.; Fiore, A.M.; Baublitz, C.B.; Follette-Cook, M.B.; Nicely, J.M.; Wolfe, G.M. Spatial and temporal variability in the hydroxyl (OH) radical: Understanding the role of large-scale climate features and their influence on OH through its dynamical and photochemical drivers. Atmos. Chem. Phys. 2021, 21, 6481–6508. [Google Scholar] [CrossRef]
  80. Zhong, X.; Shen, H.; Zhao, M.; Zhang, J.; Sun, Y.; Liu, Y.; Zhang, Y.; Shan, Y.; Li, H.; Mu, J.; et al. Nitrous acid budgets in the coastal atmosphere: Potential daytime marine sources. Atmos. Chem. Phys. 2023, 23, 14761–14778. [Google Scholar] [CrossRef]
  81. Ren, X.; Harder, H.; Martinez, M.; Lesher, R.L.; Oliger, A.; Simpas, J.B.; Brune, W.H.; Schwab, J.J.; Demerjian, K.L.; He, Y.; et al. OH and HO2 Chemistry in the urban atmosphere of New York City. Atmos. Environ. 2003, 37, 3639–3651. [Google Scholar] [CrossRef]
  82. Chen, T.; Xue, L.; Zheng, P.; Zhang, Y.; Liu, Y.; Sun, J.; Han, G.; Li, H.; Zhang, X.; Li, Y.; et al. Volatile organic compounds and ozone air pollution in an oil production region in northern China. Atmos. Chem. Phys. 2020, 20, 7069–7086. [Google Scholar] [CrossRef]
  83. Wang, W.; van der A, R.; Ding, J.; van Weele, M.; Cheng, T. Spatial and temporal changes of the ozone sensitivity in China based on satellite and ground-based observations. Atmos. Chem. Phys. 2021, 21, 7253–7269. [Google Scholar] [CrossRef]
  84. Zhang, J.; Lian, C.; Wang, W.; Ge, M.; Guo, Y.; Ran, H.; Zhang, Y.; Zheng, F.; Fan, X.; Yan, C.; et al. Amplified role of potential HONO sources in O3 formation in North China Plain during autumn haze aggravating processes. Atmos. Chem. Phys. 2022, 22, 3275–3302. [Google Scholar] [CrossRef]
  85. Johnson, M.S.; Philip, S.; Meech, S.; Kumar, R.; Sorek-Hamer, M.; Shiga, Y.P.; Jung, J. Insights into the long-term (2005–2021) spatiotemporal evolution of summer ozone production sensitivity in the Northern Hemisphere derived with the Ozone Monitoring Instrument (OMI). Atmos. Chem. Phys. 2024, 24, 10363–10384. [Google Scholar] [CrossRef]
  86. Zhang, S.; Sarwar, G.; Xing, J.; Chu, B.; Xue, C.; Sarav, A.; Ding, D.; Zheng, H.; Mu, Y.; Duan, F.; et al. Improving the representation of HONO chemistry in CMAQ and examining its impact on haze over China. Atmos. Chem. Phys. 2021, 21, 15809–15826. [Google Scholar] [CrossRef] [PubMed]
  87. Ji, D.; Gao, W.; Maenhaut, W.; He, J.; Wang, Z.; Li, J.; Du, W.; Wang, L.; Sun, Y.; Xin, J.; et al. Impact of air pollution control measures and regional transport on carbonaceous aerosols in fine particulate matter in urban Beijing, China: Insights gained from long-term measurement. Atmos. Chem. Phys. 2019, 19, 8569–8590. [Google Scholar] [CrossRef]
  88. Ren, J.; Xie, S. Diagnosing ozone-NOx-VOC sensitivity and revealing causes of ozone increases in China based on 2013–2021 satellite retrievals. Atmos. Chem. Phys. 2022, 22, 15035–15047. [Google Scholar] [CrossRef]
  89. Donzelli, G.; Suarez-Varela, M.M. Tropospheric Ozone: A Critical Review of the Literature on Emissions, Exposure, and Health Effects. Atmosphere 2024, 15, 779. [Google Scholar] [CrossRef]
  90. Shan, D.; Du, Z.; Zhang, T.; Zhang, X.; Cao, G.; Liu, Z.; Yao, Z.; Tang, K.; Liang, S. Variations, sources, and effects on ozone formation of VOCs during ozone episodes in 13 cities in China. Front. Environ. Sci. 2023, 10, 1084592. [Google Scholar] [CrossRef]
  91. Zhu, J.; Wang, S.; Gu, C.; Jiang, Z.; Zhang, S.; Xue, R.; Yan, Y.; Zhou, B. Why did ozone concentrations remain high during Shanghai’s static management? A statistical and radical-chemistry perspective. Atmos. Chem. Phys. 2024, 24, 8383–8395. [Google Scholar] [CrossRef]
  92. Xue, L.K.; Wang, T.; Gao, J.; Ding, A.J.; Zhou, X.H.; Blake, D.R.; Wang, X.F.; Saunders, S.M.; Fan, S.J.; Zuo, H.C.; et al. Ground-level ozone in four Chinese cities: Precursors, regional transport and heterogeneous processes. Atmos. Chem. Phys. 2014, 14, 13175–13188. [Google Scholar] [CrossRef]
  93. Wang, W.; Parrish, D.D.; Li, X.; Shao, M.; Liu, Y.; Mo, Z.; Lu, S.; Hu, M.; Fang, X.; Wu, Y.; et al. Exploring the drivers of the increased ozone production in Beijing in summertime during 2005–2016. Atmos. Chem. Phys. 2020, 20, 15617–15633. [Google Scholar] [CrossRef]
  94. West, J.J.; Naik, V.; Horowitz, L.W.; Fiore, A.M. Effect of regional precursor emission controls on long-range ozone transport—Part 1: Short-term changes in ozone air quality. Atmos. Chem. Phys. 2009, 9, 6077–6093. [Google Scholar] [CrossRef]
  95. Liu, H.J.; Zhao, C.S.; Nekat, B.; Ma, N.; Wiedensohler, A.; van Pinxteren, D.; Spindler, G.; Mueller, K.; Herrmann, H. Aerosol hygroscopicity derived from size-segregated chemical composition and its parameterization in the North China Plain. Atmos. Chem. Phys. 2014, 14, 2525–2539. [Google Scholar] [CrossRef]
  96. Farmer, D.K.; Cappa, C.D.; Kreidenweis, S.M. Atmospheric processes and their controlling influence on cloud condensation nuclei activity. Chem. Rev. 2015, 115, 4199–4217. [Google Scholar] [CrossRef]
  97. Chang, M.C.; Sioutas, C.; Kim, S.; Gong, H.; Linn, W.S. Reduction of nitrate losses from filter and impactor samplers by means of concentration enrichment. Atmos. Environ. 2000, 34, 85–98. [Google Scholar] [CrossRef]
  98. Eichler, M.; Michel, B.; Thomas, M.; Gabriel, M.; Klages, C.P. Atmospheric-pressure plasma pretreatment for direct bonding of silicon wafers at low temperatures. Surf. Coat. Technol. 2008, 203, 826–829. [Google Scholar] [CrossRef]
  99. Xue, C.; Zhang, C.; Ye, C.; Liu, P.; Catoire, V.; Krysztofiak, G.; Chen, H.; Ren, Y.; Zhao, X.; Wang, J.; et al. HONO budget and its role in nitrate formation in the rural north china plain. Environ. Sci. Technol. 2020, 54, 11048–11057. [Google Scholar] [CrossRef] [PubMed]
  100. Xue, C.; Ye, C.; Kleffmann, J.; Zhang, C.; Catoire, V.; Bao, F.; Mellouki, A.; Xue, L.; Chen, J.; Lu, K.; et al. Atmospheric measurements at Mt. Tai—Part I: HONO formation and its role in the oxidizing capacity of the upper boundary layer. Atmos. Chem. Phys. 2022, 22, 3149–3167. [Google Scholar] [CrossRef]
  101. Han, C.; Yang, W.; Wu, Q.; Yang, H.; Xue, X. Heterogeneous Photochemical Conversion of NO2 to HONO on the Humic Acid Surface under Simulated Sunlight. Environ. Sci. Technol. 2016, 50, 5017–5023. [Google Scholar] [CrossRef]
  102. McDuffie, E.E.; Womack, C.C.; Fibiger, D.L.; Dube, W.P.; Franchin, A.; Middlebrook, A.M.; Goldberger, L.; Lee, B.H.; Thornton, J.A.; Moravek, A.; et al. On the contribution of nocturnal heterogeneous reactive nitrogen chemistry to particulate matter formation during wintertime pollution events in Northern Utah. Atmos. Chem. Phys. 2019, 19, 9287–9308. [Google Scholar] [CrossRef]
  103. Li, Y.; Wang, X.; Wu, Z.; Li, L.; Wang, C.; Li, H.; Zhang, X.; Zhang, Y.; Li, J.; Gao, R.; et al. Atmospheric nitrous acid (HONO) in an alternate process of haze pollution and ozone pollution in urban Beijing in summertime: Variations, sources and contribution to atmospheric photochemistry. Atmos. Res. 2021, 260, 105689. [Google Scholar] [CrossRef]
  104. Wong, K.; Oh, H.J.; Lefer, B.; Rappenglück, B.; Stutz, J. Vertical profiles of nitrous acid in the nocturnal urban atmosphere of Houston, TX. Atmos. Chem. Phys. Discuss. 2010, 11, 3595–3609. [Google Scholar] [CrossRef]
  105. Wong, K.; Tsai, C.; Lefer, B.; Grossberg, N.; Stutz, J. Modeling of daytime HONO vertical gradients during SHARP 2009. Atmos. Chem. Phys. 2013, 13, 3587–3601. [Google Scholar] [CrossRef]
  106. Liu, Y.; Lu, K.; Li, X.; Dong, H.; Tan, Z.; Wang, H.; Zou, Q.; Wu, Y.; Zeng, L.; Hu, M.; et al. A Comprehensive Model Test of the HONO Sources Constrained to Field Measurements at Rural North China Plain. Environ. Sci. Technol. 2019, 53, 3517–3525. [Google Scholar] [CrossRef]
Atmosphere 17 00558 g001
Figure 1. Map of the two observation sites, Pudong (urban, PD) and Qingpu (suburban, QP), in this study (marked with asterisks).
Figure 1. Map of the two observation sites, Pudong (urban, PD) and Qingpu (suburban, QP), in this study (marked with asterisks).
Atmosphere 17 00558 g001
Atmosphere 17 00558 g002
Figure 2. Seasonal variation of HONO (ppb) (a,b) and HONO/NO2 ratio (c,d) for PD/QP in 2017–2021. The box represents the 25th to 75th percentiles, the horizon line represents the median, the circle represents average, and the 10th and the 90th percentiles are the bottom and top whiskers respectively.
Figure 2. Seasonal variation of HONO (ppb) (a,b) and HONO/NO2 ratio (c,d) for PD/QP in 2017–2021. The box represents the 25th to 75th percentiles, the horizon line represents the median, the circle represents average, and the 10th and the 90th percentiles are the bottom and top whiskers respectively.
Atmosphere 17 00558 g002
Atmosphere 17 00558 g003
Figure 3. Diurnal variations of HONO (ppb) for PD/QP in 2017–2021 (a,b).
Figure 3. Diurnal variations of HONO (ppb) for PD/QP in 2017–2021 (a,b).
Atmosphere 17 00558 g003
Atmosphere 17 00558 g004
Figure 4. Changes in HONO (ppb) with temperature (°C) over different years (2017–2021: (a–e)) at the PD and QP sites. The box represents the 25th to 75th percentiles, the horizon line represents the median, the circle represents average, and the 10th and the 90th percentiles are the bottom and top whiskers respectively.
Figure 4. Changes in HONO (ppb) with temperature (°C) over different years (2017–2021: (a–e)) at the PD and QP sites. The box represents the 25th to 75th percentiles, the horizon line represents the median, the circle represents average, and the 10th and the 90th percentiles are the bottom and top whiskers respectively.
Atmosphere 17 00558 g004
Atmosphere 17 00558 g005
Figure 5. Changes in HONO (ppb) with RH (%) over different years (2017–2021: (a–e)) at the PD and QP sites. The box represents the 25th to 75th percentiles, the horizon line represents the median, the circle represents average, and the 10th and the 90th percentiles are the bottom and top whiskers respectively.
Figure 5. Changes in HONO (ppb) with RH (%) over different years (2017–2021: (a–e)) at the PD and QP sites. The box represents the 25th to 75th percentiles, the horizon line represents the median, the circle represents average, and the 10th and the 90th percentiles are the bottom and top whiskers respectively.
Atmosphere 17 00558 g005
Atmosphere 17 00558 g006
Figure 6. 2017–2021 wind rose analysis in PD site. Color represents wind speed, radius represents frequency, and angle represents wind direction.
Figure 6. 2017–2021 wind rose analysis in PD site. Color represents wind speed, radius represents frequency, and angle represents wind direction.
Atmosphere 17 00558 g006
Atmosphere 17 00558 g007
Figure 7. Diurnal profiles of model-simulated OH chemical budgets with or without constraint on HONO in PD summer. (a) OH chemical budget simulated by the model with HONO in 2018; (b) OH chemical budget simulated by the model without HONO in 2018; (c) OH chemical budget simulated by the model with HONO in 2021; (d) OH chemical budget simulated by the model without HONO in 2021.
Figure 7. Diurnal profiles of model-simulated OH chemical budgets with or without constraint on HONO in PD summer. (a) OH chemical budget simulated by the model with HONO in 2018; (b) OH chemical budget simulated by the model without HONO in 2018; (c) OH chemical budget simulated by the model with HONO in 2021; (d) OH chemical budget simulated by the model without HONO in 2021.
Atmosphere 17 00558 g007
Atmosphere 17 00558 g008
Figure 8. Diurnal profiles of model-simulated O3 chemical budgets with or without constraint on HONO in PD summer. Other RO2 + NO stands for RO2 + NO reactions other than CH3O2 + NO. (a) O3 chemical budget simulated by the model with HONO in 2018; (b) O3 chemical budget simulated by the model without HONO in 2018; (c) O3 chemical budget simulated by the model with HONO in 2021; (d) O3 chemical budget simulated by the model without HONO in 2021.
Figure 8. Diurnal profiles of model-simulated O3 chemical budgets with or without constraint on HONO in PD summer. Other RO2 + NO stands for RO2 + NO reactions other than CH3O2 + NO. (a) O3 chemical budget simulated by the model with HONO in 2018; (b) O3 chemical budget simulated by the model without HONO in 2018; (c) O3 chemical budget simulated by the model with HONO in 2021; (d) O3 chemical budget simulated by the model without HONO in 2021.
Atmosphere 17 00558 g008
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, W.; Hu, M.; Feng, J.; Fu, Q.; Wang, S. Impacts from HONO Chemistry on Atmospheric Oxidation Capacity: A Case Study in Shanghai. Atmosphere 2026, 17, 558. https://doi.org/10.3390/atmos17060558

AMA Style

Zhang W, Hu M, Feng J, Fu Q, Wang S. Impacts from HONO Chemistry on Atmospheric Oxidation Capacity: A Case Study in Shanghai. Atmosphere. 2026; 17(6):558. https://doi.org/10.3390/atmos17060558

Chicago/Turabian Style

Zhang, Wei, Ming Hu, Jialiang Feng, Qingyan Fu, and Shunyao Wang. 2026. "Impacts from HONO Chemistry on Atmospheric Oxidation Capacity: A Case Study in Shanghai" Atmosphere 17, no. 6: 558. https://doi.org/10.3390/atmos17060558

APA Style

Zhang, W., Hu, M., Feng, J., Fu, Q., & Wang, S. (2026). Impacts from HONO Chemistry on Atmospheric Oxidation Capacity: A Case Study in Shanghai. Atmosphere, 17(6), 558. https://doi.org/10.3390/atmos17060558

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop