Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities

Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities Keding Lu, Haichao Wang, Yujie Qin, Lei Li, Chenglei Pei, Guiqian Tang, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7100046/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Nitrate radicals (NO 3 ) play a crucial role in the removal of nitrogen oxides (NO x ) from Earth's atmosphere and act as the dominant nocturnal oxidant in polluted regions, thereby influencing air quality, climate, and ecological systems. However, the vertical variations of NO 3 chemistry within the planetary boundary layer during nighttime remain poorly understood due to the stratification of nocturnal air masses and complex chemical conditions. Here, we present vertical and ground-based observations of NO 3 precursors across diverse atmospheric environments. Our results indicate that the enhanced NO 3 chemistry aloft event, defined as the NO 3 production rate above the canopy being higher than at surface levels, occurs frequently in megacities (64-72%) with a median enhancement factor of 2.7. This phenomenon likely largely promotes more rapid oxidation reactions and secondary pollutant formation in the aloft environment. We show this event is more prevalent in China and India than in the United States and Europe. However, a rapid decline in its frequency has been observed in China in recent years, closely linked to the implementation of stringent NO x emission control measures. We demonstrate that this event is attributed to the interplay between intense ground-level NOx emissions and atmospheric stability. These findings highlight the critical role of vertical gradients in nocturnal NO 3 chemistry on surface air pollution and underscore the need for comprehensive vertical measurement to support further improvement of urban air quality. Earth and environmental sciences/Environmental sciences/Environmental chemistry/Atmospheric chemistry Earth and environmental sciences/Environmental sciences/Environmental impact Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Main text Nitrate radical (NO 3 ) is a pivotal oxidant in the atmosphere, playing a significant role in climate and ecological communities ( 1 – 3 ). Originating from the chemical reactions of nitrogen dioxide (NO 2 ) and ozone (O 3 ), the formation rate of NO 3 radicals is notably high in polluted urban areas, far exceeding that in suburban or remote regions with low nitrogen dioxide (NO 2 ) concentrations( 4 ). NO 3 radicals are capable of rapidly degrading certain volatile organic compounds (VOCs) ( 2 ), especially olefin, to produce organic aerosols and contribute to the nitrate aerosol formation, and the activation of halogen chemistry via the heterogeneous reaction of dinitrogen pentoxide (N 2 O 5 ) ( 5 , 6 ). In polluted urban areas with high aerosol loading and elevated NO x levels, the heterogeneous reaction of N 2 O 5 initiated by NO 3 radicals makes a substantial contribution to nitrate aerosol pollution ( 7 – 9 ). Furthermore, despite lower NO x emission levels in Europe and the US, NO 3 radicals still play a crucial role in secondary organic aerosol formation with high efficiency ( 10 – 14 ), highlighting the importance of NO 3 radical chemistry in secondary pollution under various environmental conditions globally. We recently identified China as a hotspot for global surface nocturnal NO 3 radical oxidation by using the NO 3 production rate (PNO 3 , Eq. 1) as the proxy. PNO 3 has risen rapidly in recent years and has the potential to shift air pollution patterns ( 15 ). While different from daytime when the planetary boundary layer is typically well mixed, the nocturnal atmosphere exhibits considerable stratification vertically due to the ground cooling, leading to substantial variations in pollutant concentration and chemical processes in different layers. This means that field observations conducted at one altitude (at ground in general) are insufficient to accurately describe nighttime chemistry throughout the boundary layer( 16 ). PNO 3 = k NO2+O3 [NO 2 ][O 3 ] Eq. 1 During the nighttime, vertical stratification may lead to gradients in NO 2 and O 3 , but the concentration of total oxidants (O x = NO 2 + O 3 ) tend to be approximately constant with height. The vertical partitioning of NO 2 and O 3 may shift due to the emissions( 17 – 20 ), which happens in the surface layer due to anthropogenic and soil emissions of NO x , and in the upper mixing layer due to the injection of NO x emission sources such as power plants. Generally, in the absence of emission perturbation aloft, the concentrations of NO and NO₂ exhibit a decreasing trend with the increase of altitude, while the concentration of O₃ shows an opposite increasing trend( 19 ). Note that the titration reaction of NO and NO 3 is fast, often resulting in low concentrations of NO 3 radicals in the NO x source regions, which limits NO 3 oxidation potential in the surface layer, which is common in urban regions ( 21 ). Nevertheless, NO 3 chemistry may be significantly enhanced in regions with the absence of NO above the surface layer. To understand the vertical oxidation at nighttime, a series of vertical field studies of NO 3 and N 2 O 5 measurements, using advanced platforms like aircraft and tall towers ( 18 – 20 , 23 – 26 ), and model simulations were conducted ( 16 , 22 ). These results revealed a significant altitude dependence of NO 3 , precursors, and scavengers, and found the concentration of NO 3 and N 2 O 5 is higher aloft than on the ground ( 18 , 19 , 23 – 25 ), indicating an active nighttime chemistry aloft. However, due to the limited vertical measurements and datasets, it remains a persistent challenge to evaluate the vertical evolution of NO 3 oxidation over the long term and across diverse environments at the current stage. Here, we collected a vertical observational dataset of NO 2 and O 3 from tower that spans different environmental conditions from clean to polluted regions, including Guangzhou, Shenzhen, Beijing in China, and Erie, CO in the U.S., as well as surface NO 2 and O 3 dataset globally (Methods). Using PNO 3 as the indicator( 15 , 26 ), we characterized the vertical distribution of nocturnal NO 3 radical oxidation capacity and causes. We further built a comprehensive framework to diagnose and evaluate the global trend of vertical NO 3 radical chemistry by using the surface measurement dataset from 2014–2021, linking it to emission reductions over the past decade. Results Characterization of enhanced PNO 3 aloft event. Higher PNO 3 aloft compared with the ground means that the potential of enhanced nocturnal oxidation chemistry in the upper mixing layer, which will cause more air pollutants formation and impact on ground pollution. In order to understand the possibility of enhanced PNO 3 in the upper mixing layer and its characteristics and influencing factors, we classified the observed vertical distribution of PNO 3 into two types. Specifically, the enhanced PNO 3 aloft event (EPE) was defined if the observed PNO 3 at any height (over 20 m, AGL) in the upper mixing layer was greater than 30% of the ground PNO 3 , this threshold exceeds the double uncertainty from the instrument of NO x and O 3 . The corresponding non-enhanced PNO 3 event (NEPE) was defined when the observed PNO 3 in the upper mixing layer is not significantly higher than near ground, with the ratio of PNO 3 at any layer aloft to the surface lower than 1.3. Figure 1 a shows the proportion of EPE in the Guangzhou, Beijing, and Shenzhen tower in China reached 72%, 64%, and 68%, respectively, which is much higher than the results in the Erie tower in the United States (16%). Considering that the data from the three sites in China have good seasonal coverage, while the data in the US is only available in winter, we further calculated the proportion of EPE appearing only in winter in China, which still much higher than that in the Erie tower (Extended Data Fig. 1 ). In order to further understand the occurrence mechanism of EPE at nighttime, we use the relative concentration of NO 2 and O 3 on the ground as a standard to simplified the vertical distribution of air masses. We explored all possible vertical distributions of NO 2 and O 3 based on their relative concentration on the ground (Methods and Extended Data Fig. 2 ). When the ground NO 2 > O 3 , we define it as the NO x -saturated scenario, and the NO x -limited scenario defined as the ground NO 2 < O 3 . Figure 1 a indicates that the probability of EPE in NO x -saturated scenarios is much higher than in NO x -limited scenarios, with consistent results in Guangzhou, Beijing, and Eric, CO, and the EPE mainly occurs in four specific types of vertical structures (Extended Data Fig. 3 ). In Shenzhen, the proportion of EPE in both NO x -saturated and NO x -limited scenarios is relatively high, and the cause will be discussed later. This phenomenon aligns with the theoretical expectations. It is well-known that NO x primarily originates from ground-level emissions. Thus, NO x concentrations generally decrease with altitude at night, while O 3 concentrations tend to increase with height since it can be less titrated by NO aloft. Under the premise of the relative conservation of the vertical concentration of O x since afternoon, if the ground-level NO 2 concentration exceeds that of O 3 , that means the concentrations of NO₂ and O₃ are expected to reach equilibrium inevitably at a particular altitude, and the production rate of nitrate radicals (PNO₃) is anticipated to achieve its maximum value. However, the observed results did not perfectly match theoretical predictions for two main reasons. Firstly, vertical observations are limited to several specific layers, and there may be a lack of observations where PNO 3 peaks occur. Secondly, some occurrences of PNO 3 peak may not have been included in valid results due to the threshold for the enhanced type being set at 30%. If we lower the threshold to 10%, the proportion of the EPE in NO x -saturated scenarios across different regions increases, with an average of 86% (Extended Data Fig. 4 ). When ground-level NO x is lower than O 3 , PNO 3 is theoretically expected to decrease with altitude as NO x concentrations decline and O 3 increases. However, O x is not always conserved vertically( 27 ). On one hand, the deposition of O 3 and NO 2 leads to a reduction in ground-level O x concentration. On the other hand, differences in the conversion and removal rates of NO 2 and O 3 at various altitudes may cause actual observations to deviate from theoretical expectations. Additionally, the transportation and injection of NO x emissions from elevated NO x emission sources or other urban plumes like power plant( 28 ) can lead to a redistribution of NO x as well as O x in the vertical scale, resulting in increasing NO 2 and thus enhanced nocturnal oxidation chemistry aloft, as frequently observed at the Shenzhen tower( 29 , 30 ). However, the occurrence of this phenomenon is highly related to the surroundings and varies depending on the urban environment and emission characteristics. For example, under NO x -limited scenarios, the proportion of EPE in Guangzhou, Beijing, and Shenzhen is significantly higher than in Eric (7%), highlighting the considerable impact of high-altitude NO x injection from urban human activities on the vertical structure of nighttime atmospheric oxidation. We show that the overall median RPNO 3 (the ratio of the maximum PNO 3 value in the upper mixing layer to the ground) in the EPE in the three Chinese megacities sites reached 2.7, means a significant enhancement of PNO 3 over the megacities. Although the EPE occurs under both NO x -saturated and NO x -limited scenarios, there is a notable difference in the intensity of nighttime chemistry enhancement (Fig. 1 b). All sites (except Shenzhen) exhibited significantly higher PNO 3 enhancement under NO x -saturated compared to the NO x -limited scenarios. Specifically, the median RPNO 3 in Guangzhou, Beijing, and Eric under NO x -limited and NO x -saturated scenarios were 2.4/3.2, 1.7/2.7, and 1.4/2.9, respectively. Due to the significant impact of high-altitude NO x emissions injection, the Shenzhen station (2.0/1.8) showed an inconsistent trend. In addition, the average proportion of RPNO 3 greater than 2 in these four regions can reach 52%, and particularly prominent in Beijing (51%) and Guangzhou (72%), where the sites located in the central of urban agglomerations, higher than the suburban sites of Shenzhen (42%) and Erie, CO (44%). This result highlights the crucial role of NO x emissions in regulating EPE events. Under high NO x conditions, it is more likely that the chemical activity of NO 3 at high altitudes far exceeds that near the ground. We further revealed the pivotal influence of daytime temperature and the boundary layer height on the characteristics of EPE. As depicted in Fig. 2 , by taking the Guangzhou tower observation as an example, the higher temperatures at daytime correlate with increasing O x levels and a lower nocturnal boundary layer height. High temperatures speed up the photochemistry to produce more oxidants, and higher temperatures during the daytime are typically associated with less cloud, and fast decoupling of the nocturnal boundary layer and residual layer at night ( 31 ). These lead to a more pronounced difference in PNO 3 levels within the boundary layer and the residual layer at night. In addition, low nocturnal boundary layer height often implies weaker vertical turbulent mixing and stable atmospheric condition, leading to larger vertical gradients of NO x and O 3 at the vertical scale, further exacerbating the differences in PNO 3 at the vertical scale( 32 ). When the highest measurement platform at 488 m is also within the nocturnal boundary layer, the vertical variation in PNO 3 concentration is relatively subtle, with a maximum ratio of 2.0 between the elevated and ground-level PNO 3 (at 168 m/surface, shown in Fig. 2 a). However, when the nocturnal boundary layer height decreases, for example, drops below 120 m as shown in Fig. 2 c, the residual layer PNO 3 concentration can be 2.9 times higher than the near-surface levels and remains consistently higher at 118 m and 168 m. Moreover, due to the limited number of observational points across the entire vertical scale, a refined description of the vertical profile changes is not feasible. At unmonitored heights (e.g., from 168–488 m), higher PNO 3 values may occur, indicating the need for high spatial resolution in vertical measurements of tower systems to fully quantify the depth of the highly reactive zone of NO 3 chemistry at night. Environmental impacts of enhanced PNO 3 aloft event. We found the proportion of nocturnal ozone concentrations exceeding 10 ppb above 118 m is over 54% and exhibits a rapid upward trend with increasing height (Extended Data Fig. 5 ). This indicates that the lifetime of NO is restricted to under 4 minutes, with a rate constant of 1.73×10 − 14 molecule − 1 s − 1 cm 3 for the NO + O 3 reaction at 298 K. Therefore, the nocturnal residual layer chemistry is minimally affected by the near-surface NO emissions. Using Guangzhou tower as an example, quantitative calculations of O x depletion (Methods) at different altitudes reveal the weaker nocturnal O x loss at the ground and 488 m levels, compared with the O x deficit occurs at 118 m and 168 m (Figure. 3a). This indicates a significant removal process of O x occurred in the middle layers, these O x may convert to NO 3 and N 2 O 5 and consumed by the following chemistry, which is in good agreement with the observed distribution of PNO 3 . This smallest O x deficit on the surface may be largely due to the less efficient NOx removal via NO 3 chemistry. The vertical O x deficit was also confirmed by the results observed at Shenzhen tower and Beijing tower (Fig. 3 b, c). The lifetime is an important index for reflecting the role of NO 3 and N 2 O 5 chemistry in forming secondary pollutants. Previous work has shown significant differences in NO 3 and N 2 O 5 lifetimes between urban areas and remote regions( 7 , 33 – 35 ). Observations from the Guangzhou tower indicate that particulate matter concentration levels remain high at 20–40 µg/m 3 , albeit lower compared to ground levels, as well as the NO 3 -reactive VOC species ( 36 , 37 ). We estimate that the typical nocturnal lifetimes of NO 3 radicals and N 2 O 5 near the urban surface are short, caused by NO 3 + VOC and N 2 O 5 uptake, at approximately 1–5 minutes and 10–30 minutes, respectively. However, they are two times longer on average in the residual layer due to the lower abundance of NO 3 reactants. This is similar to the case observed in Houston ( 38 ), Los Angeles ( 39 ), Eastern US( 33 ), London ( 40 ), and Seoul ( 41 ), but significantly lower than those in remote regions' residual layer ( 42 ). Therefore, we argue that in areas with particulate matter pollution happens with relative high frequency, the loss of NO 3 in the nocturnal boundary layer and residual layer is still fast to produce secondary pollutants on average, and does not act as a reservoir to a large extent. However, in relatively clean areas, N 2 O 5 may still act as a reservoir for NO x ( 33 ). In the polluted urban areas of China, the chemistry of NO 3 and N 2 O 5 in the nocturnal residual layer is reactive, and the oxidation of VOCs by NO 3 and the heterogeneous reactions of N 2 O 5 could significantly contribute to the formation of secondary pollution ( 43 , 44 ). For example, the contribution of N 2 O 5 heterogeneous reactions in the residual layer to near-surface nitrate in the Beijing area is important ( 20 , 45 ). Moreover, recent findings have shown that the burst of active chlorine chemistry during the COVID period has significantly enhanced atmospheric oxidation potential and the formation of secondary organic aerosols ( 46 ). Although synchronous observations are lacking in the residual layer to quantify these contributions, it is anticipated that the formation of nitrate aerosol and active halogen species above the urban residual layer may be like the undisturbed NO-free conditions near the surface( 47 ). The simulation results from WRF-CMAQ effectively validate this speculation by taking four Chinese city clusters as an example (Methods). Figure 4 shows that the enhancement of PNO 3 aloft compared with the surface at EPE in four city clusters is much higher than those at NEPE condition, which is consistent with the observations in general. In both NO x -saturated and limited scenarios, NO 3 chemistry in the upper mixing layer is more active due to reduced influence from NO, thus the ratio of the maximum NO 3 oxidation loss rate (here including NO 3 + VOC and N 2 O 5 uptake) in the upper mixing layer to the ground is greater than 1.0 in four typical Chinese city cluster. It is worth noting that under NO x -saturated scenarios, due to the significant enhancement of PNO 3 in the upper mixing layer, the ratio of the maximum NO 3 oxidation loss rate in the upper mixing layer to the ground further increases, especially in BTH and CY regions, the ratio reach up to 14.2 and 20.7, respectively. This further highlight the critical role of EPE on the secondary air pollutants formation above the canopy of urban regions. For the inter-comparison, the vertical loss of NO 3 at night in Eric tower was calculated based on the field observation dataset, and showed a consistent and similar loss pattern as model result presented (Extended Data Fig. 6 ). The long-term trend of enhanced PNO 3 aloft event. With the ongoing global efforts to reduce and control NO x emissions, the proportion of NO x -saturated scenario is gradually decreasing. Therefore, the vertical distribution pattern of PNO 3 will systematically shift to the NEPE. As shown in Fig. 5 a, the long-term observation in the Guangzhou tower confirmed this change with an overall increase in NEPE and decreasing in EPE (from 99–47%) over 2014–2020. Since the long-term vertical measurement of NO 3 precursors is limited globally, and considering that under high NO x scenario, the observed proportion of EPE is much higher with a larger enhancement of PNO 3 , thus the fraction of NO x -saturated scenario can be representative of the EPE to large extent. Here we used the fraction of NO x -saturated scenario as a proxy for the EPE, and Fig. 5 b shows the average fraction of NO x -saturated scenario is much higher in China and India compared with US and EU. This indicates that due to high NO x emissions in China and India, the probability of enhanced NO 3 chemistry occurring over urban clusters is higher than that in the United States and Europe. Concerning the four Chinese city clusters, the average fraction of NO x -saturated scenario is higher in Peral River Delta (PRD) and the Chengdu-Chongqing area (CY), with both fractions at 46% ± 17%. Figure 5 c reveals a consistent downward trend in the average proportion of NO x -saturated scenarios across the US, EU, and China. Among these regions, China demonstrates the most pronounced reduction, especially within the BTH area of the four city clusters, where a decline rate of 2.6% per year is observed. This trend shows good consistency with the reduction of NO x during the past years ( 48 ). Due to the limited dataset with fewer sites and short time coverage, the trend for India is not further assessed. We should note that even if the trend showed a decrease in NO x -saturated scenario with an indicative of the decrease in EPE. The pattern of enhanced PNO 3 aloft still accounts for nearly half of the total in China just like the Guangzhou Canton tower case presented in Fig. 5 a. In addition, we show that there is a consistently higher fraction of high NO x -saturated scenario in urban than non-urban regions, with a faster decrease of the fraction in urban regions (Extended Data Fig. 7). Therefore, from a long-term perspective, the EPE would be still important in causing air pollution in urban regions, and this change trigged by NO x reduction may have implications for atmospheric chemistry and air quality management on a large scale. Discussion and implications In this study, based on the comprehensive dataset, we reveal a special vertical distribution pattern of nighttime chemical oxidation, clarified the boundary layer dynamic mechanism and the response of vertical differences of nocturnal NO 3 chemistry in the boundary layer on the anthropogenic emissions. The result highlights the large different vertical nocturnal oxidation patterns in high and low NO x emission areas. We thus propose a conceptual framework to depict the unique characteristics of NO 3 chemistry and its vertical dependence in varied environments. As shown in Fig. 6 , in urban regions with intensive anthropogenic emissions, NO 3 can be rapidly formed by both elevated NO 2 and O 3 above the city canopy, and also free from local NO titration. These two aspects provide an ideal environment for NO 3 to react with VOCs and N 2 O 5 uptake with high efficiency, and may cause fast secondary pollutant formation, including nitrate aerosol, secondary organic aerosol, and reactive chlorine precursors that enhance the following daytime photochemistry( 49 – 52 ). This may contribute to the deterioration of surface air pollution with rapid growth in pollutant concentrations. Importantly, this event happened with very high frequencies in intensive NOx emission regions, highlighting the critical but overlooked role of NO 3 chemistry above these regions. By contrast, PNO 3 is relatively low aloft compared with the ground in rural regions with weak NO x emission, and NO titration has a smaller impact on the surface, causing the key area for nighttime oxidation to be at or near the surface, and may be a smaller role aloft. This pattern should be more representative of low anthropogenic emission regions( 53 ). We should note that although PNO 3 is a proxy of the nocturnal atmospheric oxidation upper limit, it may overestimate the real atmospheric oxidation capacity in some conditions as indicated by the model results (Fig. 4 ). In areas with intensive anthropogenic emissions, NO 3 is titrated by NO to form NO 2 rather than effective NOx removal. And NO 3 and N 2 O 5 may be a reservoir of active nitrogen species rather than an oxidizing agent at low VOC and particulate matter loading regions ( 17 ). Nevertheless, the aim of this study was not to accurately quantify nocturnal atmospheric oxidation, but to systematically assess the vertical pattern and evolution of the nocturnal oxidation. Finally, we highlight that more detailed, comprehensive field experiments and model simulations with more refined spatial resolution are needed, to identify the role of nighttime chemistry in the upper layer and residual layer on the surface air pollution in high NO x urban regions. Better understanding of residual layer chemistry holds potential to improve strategies for regional air quality mitigation as well as the air pollution forecast. Methods Vertical observation dataset We obtained vertical observation datasets (NO 2 , O 3 , and temperature) from four in different regions in different regions, including Guangzhou, Shenzhen, Beijing in China, and Erie, CO in the U.S. The vertical observation datasets from Guangzhou, Shenzhen, and Beijing tower were fixed-point at three to four heights, and the tower in Eric, CO was continuous vertically. The datasets from different towers span different periods, ranging from 2011 to 2022. Vertical observations were conducted within 500 m and time resolution was 1 hour. Detailed descriptions of the vertical observations are listed in Supplementary Text 1 and Extended Data Table 1. To eliminate observational outliers and ensure complete vertical observational data at the same time, we excluded profiles based on the following criteria, referring to previous literature( 15 ): ( 1 ) NO 2 and O 3 concentrations were less than 0 ppbv or greater than 500 ppbv. ( 2 ) For Guangzhou Shenzhen, and Beijing tower, which have only several vertical levels, a profile with missing NO 2 or O 3 data at any level was excluded. ( 3 ) For the tower in Eric, CO, where continuous vertical observations were conducted, data was initially averaged every 20 m; The profile was excluded if there were missing NO 2 or O 3 values after averaging( 27 ). Ground observation dataset The hourly observational data of ground-level NO 2 and O 3 at 2024 stations in China were obtained from the China National Environmental Monitoring Center network. Concurrently, data for the United States and the European Union were collected from the Environmental Protection Agency Air Quality System monitoring, including 469 and 2643 stations, respectively. In addition, data for India at 267 stations are available from the Central Control Room for Air Quality Management. The time range is from 2014 to 2021. To ensure the reliability of ground observation data, we excluded data based on the following criteria ( 15 ): ( 1 ) The values less than 0 ppbv or greater than 500 ppbv. ( 2 ) The hourly standardization (calculated as \(\:{z}_{i}=\frac{{x}_{i}-\stackrel{-}{x}}{\sigma\:}\) , where \(\:{x}_{i}\) is the hourly data, \(\:\stackrel{-}{x}\) represents the monthly mean, σ is the standard deviation of each month) value exceeding 5. ( 3 ) Showing minimal daily variation (the difference between the maximum and minimum values within a day is less than 2 ppbv). ( 4 ) At least 4 out of 5 consecutive hours have the same value. ( 5 ) Unrealistically large peaks are observed in the time series. ( 6 ) The effective hours at night (20:00–04:00) are less than less than 75% (6 h), effective days are less than 60% (18 d) per month (30 d), and effective days are less than 60% (219 d) per year. These criteria removed 2.9%, 17.7%, 24.7%, and 41.9% of the hourly data in China, the European Union, the United States, and India, respectively. According to the rules provided by the Tropospheric Ozone Assessment Report (TOAR), sites are categorized as urban, suburban, and rural based on three parameters (population density, nighttime lights, and NO 2 column) ( 54 ). The categorization criteria are as follows: ( 1 ) Urban sites are characterized by population densities exceeding 1000 people km − 2 , nighttime lights greater than 60, and nighttime lights with 25 km radius of the monitoring site equal 63. ( 2 ) Suburban sites exhibit population densities ranging from 200 to 1000 people km − 2 , nighttime lights below 60, and nighttime light within a 5 km radius of the monitoring site exceeding 25. ( 3 ) Rural sites have population densities equal to or less than 200 people km − 2 , nighttime lights within a 5 km radius of the monitoring site below 25, and NO 2 column densities less than 8x10 15 molecules cm − 2 . Reanalysis dataset We used the boundary layer height from the fifth-generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis dataset of the global climate (ERA5). This dataset is generated through the assimilation of model data with various observations such as radiosonde and satellite data. ERA5 dataset provides comprehensive coverage on a global scale, featuring a horizontal resolution of 0.25° x 0.25°, a temporal resolution of 1 hour, and a vertical resolution comprising 37 standard pressure layers. For our study, we selected the Planetary Boundary Layer Height (PBLH) data for January, April, July, and October from 2014 to 2020 for analysis of the Guangzhou tower. Enumerating all vertical patterns of NO 2 and O 3 based on ground relative concentration. According to the relative concentrations of ground-level NO 2 (gNO 2 ) and O 3 (gO 3 ), two scenarios can be distinguished: one where the gNO 2 gO 3 . On this basis, there are multiple vertical distribution patterns for NO 2 and O 3 , which are mainly influenced by their vertical distribution and the relative concentration at high altitudes (hNO 2 and hO 3 ). Therefore, based on the three classification criteria, we use an exhaustive approach to list all possible vertical distribution patterns of NO 2 and O 3 (Extended Data Table 2). Firstly, according to the relative concentrations of gNO 2 and gO 3 , they can be divided into two categories: gNO 2 gO 3 . Then, further classification is carried out based on the vertical distribution of O 3 and NO 2 concentrations. In general, the concentration of NO 2 decreases with height, while the concentration of O 3 increases with height. However, in certain special cases, their vertical distributions may change. For instance, when the upper atmosphere is affected by transportation of NO x emissions, NO 2 may show an increasing distribution with height, while O 3 may exhibit a decreasing distribution. Additionally, dry deposition can also influence the vertical distribution of NO 2 and O 3 . Therefore, both O 3 and NO 2 concentrations can either increase or decrease with altitude. When O 3 concentration increases with height, it means that the concentration of O 3 at high altitude is greater than that at ground level (hO 3 > gO 3 ), NO 2 concentration may either increase (hNO 2 > gNO 2 ) or decrease (hNO 2 < gNO 2 ) with height. Conversely, when O 3 concentration decreases with height (hO 3 < gO 3 ), NO 2 concentration can also either increase or decrease with height. Furthermore, the relative concentration of gNO 2 and gO 3 , as well as their vertical distribution, will affect the relative concentration of high-level NO 2 (hNO 2 ) and O 3 (hO 3 ). Therefore, we further classify into two categories based on the relative concentration of hNO 2 and hO 3 : hNO 2 > hO 3 and hNO 2 < hO 3 . Overall, according to the above classification criteria, there are 14 possible vertical distribution patterns for NO 2 and O 3 , which account for 99.7%, 94.8%, 99.7%, and 100% of the observed data in Guangzhou, Shenzhen, Beijing, and Eric and CO, respectively. However, some special cases are not included, where the concentrations of NO 2 and O 3 are equal at ground-level or at high-level, or where NO 2 and O 3 remains unchanged in the vertical direction. Due to their rarity, these cases are not considered in this study. Then we categorize all observation data based on the ground-level and highest observation altitude NO 2 and O 3 concentrations (gNO 2 , gO 3 , hNO 2 , and hO 3 ), and calculate the occurrence probability of the enhanced PNO 3 aloft event (EPE) for each category. It is worth noting that for some cases where EPE did not occur, we believe the reason may be that the peak of PNO 3 did not appear at the maximum observation height. Therefore, when EPE occurs at moderate heights, we will also consider it as an EPE in this category. The definition of O x residual capacity. The residual capacity of nighttime O x at different heights is defined as the ratio of the average concentration of O x at nighttime (20:00–04:00 LT) to the average concentration of O x in the afternoon (14:00–17:00 LT). Due to the concentration of O x reaches is daily peak between 14:00–17:00 and the vertical mixing will be strongest( 31 ). WRF-CMAQ CMAQ version 5.2 was employed to simulate air quality across China, with a horizontal resolution of 36 km and 18 vertical layers. The SAPRC07 mechanism was used for gas-phase chemistry, alongside the Aero6 module for aerosol processes( 55 , 56 ). The simulation period spanned from September 26 to November 3, 2019, with three spin-up days. Meteorological fields were generated using WRF version 4.2, driven by NCEP FNL reanalysis data at 0.25° × 0.25° resolution. Anthropogenic emissions were obtained from the Multi-resolution Emission Inventory for China (MEIC v1.3, available at http://www.meicmodel.org , last access: 17 June 2024) ( 57 ), while biogenic emissions were estimated using MEGAN version 2.1( 58 ). Emissions from open biomass burning were derived from the FINN database (FINNv1.5; https://www2.acom.ucar.edu/modeling/finn-fire-inventory-ncar , last access: 17 June 2024) ( 59 ). The Integrated Reaction Rate (IRR) module in CMAQ was used to quantify the contributions of different chemical processes to the radical budget ( 60 ). This tool calculated the real-time production rates of radicals through various chemical pathways, helping assess their roles in pollutant formation. Extended Data Table 3 lists the NO 3 -involved gas-phase reactions in CMAQ. Declarations Data Availability. The source data generated in this study have been deposited in the figshare repository under accession code XXX. The data of the measurements in this study could be obtained upon request by the corresponding author ( [email protected] ). Code Availability. The main figures are produced by Python. The code for the model simulation can be obtained from the figshare repository under accession code XXX. Acknowledgments. H.C.W. received financial support from the National Key Research and Development Program of China (2023YFC3710900), the Guangdong Natural Science Funds for Distinguished Young Scholar (2024B1515020075). K.L. received financial support from the National Natural Science Foundation of China (grants 22325601, 22325201, 22221004), the National Research Program for Key Issue in Air Pollution Control (grant 2023YFC3706100). Author Contributions Statement. K.D.L., H.C.W., S.J.F., and S.S.B. conceived the study. Y.J.Q., and H.C.W. analyzed the data and wrote the manuscript with inputs from X.R.C., X.L., Y.M.L., Z.B.S., B.Y., Y.J.T. and Y.H.Z. C.L.P. and L.L. provide the vertical dataset. M.M.Q. provided the CMAQ model simulation result. All authors contributed to the discussed results and commented on the manuscript. Competing Interests Statement. The authors declare no competing interests. References S. S. Brown, J. Stutz, Nighttime radical observations and chemistry. 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Supplementary Files Supplementary250706final.docx Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities ExtendedData.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7100046","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":490896945,"identity":"84055d9b-fb29-489e-92b5-4ba90767eabb","order_by":0,"name":"Keding 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1","display":"","copyAsset":false,"role":"figure","size":95870,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePNO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e \u003cstrong\u003eenhancement in different towers under varies NO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ex\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e level condition. \u003c/strong\u003ePanel \u003cstrong\u003ea \u003c/strong\u003eshow\u003cstrong\u003e \u003c/strong\u003ethe proportions of NO\u003csub\u003ex\u003c/sub\u003e-saturated and limited scenarios, and the proportion of enhanced PNO\u003csub\u003e3\u003c/sub\u003e aloft events (EPE). The black percentage on the right indicates the proportions of NO\u003csub\u003ex\u003c/sub\u003e-saturated and limited scenarios. The red percentage on the right side represents the proportion of EPE under NO\u003csub\u003ex\u003c/sub\u003e-saturated and limited scenarios. The red percentage above the column indicates the overall proportion of EPE in each region. Panel \u003cstrong\u003eb\u003c/strong\u003e show the enhancement ratio under different NO\u003csub\u003ex\u003c/sub\u003e scenarios. Here the RPNO\u003csub\u003e3\u003c/sub\u003e represents the ratio of the maximum PNO\u003csub\u003e3\u003c/sub\u003e value in the upper mixing layer to the ground.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/22784f3643fb12e9ac31e732.png"},{"id":87823426,"identity":"e2682de4-3534-4ad2-8acd-da55ce5a97a5","added_by":"auto","created_at":"2025-07-29 11:24:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96715,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe impact of boundary layer height and temperature on the enhanced PNO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e event on Guangzhou tower. \u003c/strong\u003ePanel \u003cstrong\u003ea-c \u003c/strong\u003eshows the vertical distribution of PNO\u003csub\u003e3\u003c/sub\u003e with the nocturnal boundary layer height ≥500 m, ≥120 m and \u0026lt;500 m, and \u0026lt;120 m, respectively. The O\u003csub\u003ex\u003c/sub\u003e and T\u003csub\u003emax\u003c/sub\u003e indicate the corresponding average level of total oxidants and just-experienced daily maximum temperature. R represents the ratio of the maximum PNO\u003csub\u003e3\u003c/sub\u003e to the ground (RPNO\u003csub\u003e3\u003c/sub\u003e). N shows the number of valid data points. PBLH is the planetary nocturnal boundary layer height.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/97485f104da670c2da5b9626.png"},{"id":87824143,"identity":"4c0f5f39-ca77-4f90-bb16-71da3f3b7204","added_by":"auto","created_at":"2025-07-29 11:32:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe observed deficit of O\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ex\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e loss at different heights in different towers in China. \u003c/strong\u003ePanel \u003cstrong\u003ea-c\u003c/strong\u003e shows the\u003cstrong\u003e \u003c/strong\u003eO\u003csub\u003ex\u003c/sub\u003e residual capacity at Guangzhou, Shenzhen, and Beijing tower, respectively. The definition of O\u003csub\u003ex\u003c/sub\u003e residual capacity is given in Methods. The bar and error bars show the mean values and standard deviations, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/00785daa53580b3e44ddc8f4.png"},{"id":87823428,"identity":"9b19a765-5281-43b3-9aec-ce7553f4f5a3","added_by":"auto","created_at":"2025-07-29 11:24:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":271823,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe modeled production and the targeted loss rate (NO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e+VOC and N\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e uptake) of NO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e \u003cstrong\u003ein the four major urban agglomerations in China. \u003c/strong\u003ePanel\u003cstrong\u003e a-d \u003c/strong\u003erepresents the modeled EPE in the NO\u003csub\u003ex\u003c/sub\u003e-limited scenario, and panel \u003cstrong\u003ee-h \u003c/strong\u003erepresents the EPE under the NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario. The value of max/surface in each panel represents the ratio of the maximum NO\u003csub\u003e3\u003c/sub\u003e loss rate of the upper mixing layer to the surface loss rate. The BTH, PRD, YRD, and CY are the Beijing-Tianjin-Hebei region, Pearl River Delta, Yangtze River Delta, and Chengdu-Chongqing region, respectively.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/5a22e1f1a7b71f96008d9060.png"},{"id":87823424,"identity":"d72405a7-fa7f-4f16-b65a-c40e1a85c459","added_by":"auto","created_at":"2025-07-29 11:24:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":119347,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe evolution and trend of PNO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e during the past years across the globe. \u003c/strong\u003ePanel \u003cstrong\u003ea\u003c/strong\u003e show the observed annual trend of PNO\u003csub\u003e3\u003c/sub\u003e patterns during 2014-2020 in the Guangzhou Tower. Panel\u003cstrong\u003e b\u003c/strong\u003e and \u003cstrong\u003ec\u003c/strong\u003e show the average fraction of high NO\u003csub\u003ex\u003c/sub\u003e scenario and its trend based on global surface observation during 2014-2021 in the US, EU, India, China, and four Chinese city clusters including the Yangtze River Delta (YRD), Beijing-Tianjin-Hebei area (BTH), and Chengdu-Chongqing area (CY), and Peral River Delta (PRD), respectively.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/f3e9121b631f0c391aa65c4b.png"},{"id":87823429,"identity":"8b192f98-2268-401e-abeb-1393c665f34a","added_by":"auto","created_at":"2025-07-29 11:24:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":203094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe concept of the vertical profile of nitrate radical chemistry in the nocturnal boundary layer.\u003c/strong\u003e Illustration of main vertical distributions of NO\u003csub\u003e3\u003c/sub\u003e production rates and NO\u003csub\u003e3\u003c/sub\u003e precursors in high (a) and low NOx emission regions (b). A hotspot of NO\u003csub\u003e3\u003c/sub\u003e chemistry with high PNO\u003csub\u003e3\u003c/sub\u003e above the urban regions highlights the importance of NO\u003csub\u003e3\u003c/sub\u003e chemistry in urban air aloft that may be a source region for secondary air pollution.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/a2a95ab5bccf3f14dae1c648.png"},{"id":87825207,"identity":"b75ad4ee-0565-4dd5-bc5b-082b26ca6036","added_by":"auto","created_at":"2025-07-29 11:40:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2014081,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/ea92a781-2404-4684-9909-09f6fb8fca23.pdf"},{"id":87823422,"identity":"4c8ebe65-6229-46f3-9505-9983fc46c68e","added_by":"auto","created_at":"2025-07-29 11:24:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15211,"visible":true,"origin":"","legend":"Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities","description":"","filename":"Supplementary250706final.docx","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/062435e618fdd721867ab834.docx"},{"id":87824144,"identity":"2df140e1-3cd4-49b0-9be4-22e362a7a5a4","added_by":"auto","created_at":"2025-07-29 11:32:46","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":404443,"visible":true,"origin":"","legend":"","description":"","filename":"ExtendedData.docx","url":"https://assets-eu.researchsquare.com/files/rs-7100046/v1/b92bdfa3e9c2c4601e160cc7.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities","fulltext":[{"header":"Main text","content":"\u003cp\u003eNitrate radical (NO\u003csub\u003e3\u003c/sub\u003e) is a pivotal oxidant in the atmosphere, playing a significant role in climate and ecological communities (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Originating from the chemical reactions of nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e) and ozone (O\u003csub\u003e3\u003c/sub\u003e), the formation rate of NO\u003csub\u003e3\u003c/sub\u003e radicals is notably high in polluted urban areas, far exceeding that in suburban or remote regions with low nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e) concentrations(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). NO\u003csub\u003e3\u003c/sub\u003e radicals are capable of rapidly degrading certain volatile organic compounds (VOCs) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), especially olefin, to produce organic aerosols and contribute to the nitrate aerosol formation, and the activation of halogen chemistry via the heterogeneous reaction of dinitrogen pentoxide (N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In polluted urban areas with high aerosol loading and elevated NO\u003csub\u003ex\u003c/sub\u003e levels, the heterogeneous reaction of N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e initiated by NO\u003csub\u003e3\u003c/sub\u003e radicals makes a substantial contribution to nitrate aerosol pollution (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Furthermore, despite lower NO\u003csub\u003ex\u003c/sub\u003e emission levels in Europe and the US, NO\u003csub\u003e3\u003c/sub\u003e radicals still play a crucial role in secondary organic aerosol formation with high efficiency (\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), highlighting the importance of NO\u003csub\u003e3\u003c/sub\u003e radical chemistry in secondary pollution under various environmental conditions globally.\u003c/p\u003e\u003cp\u003eWe recently identified China as a hotspot for global surface nocturnal NO\u003csub\u003e3\u003c/sub\u003e radical oxidation by using the NO\u003csub\u003e3\u003c/sub\u003e production rate (PNO\u003csub\u003e3\u003c/sub\u003e, Eq.\u0026nbsp;1) as the proxy. PNO\u003csub\u003e3\u003c/sub\u003e has risen rapidly in recent years and has the potential to shift air pollution patterns (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). While different from daytime when the planetary boundary layer is typically well mixed, the nocturnal atmosphere exhibits considerable stratification vertically due to the ground cooling, leading to substantial variations in pollutant concentration and chemical processes in different layers. This means that field observations conducted at one altitude (at ground in general) are insufficient to accurately describe nighttime chemistry throughout the boundary layer(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePNO\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003ek\u003c/em\u003e\u003csub\u003eNO2+O3\u003c/sub\u003e[NO\u003csub\u003e2\u003c/sub\u003e][O\u003csub\u003e3\u003c/sub\u003e] Eq.\u0026nbsp;1\u003c/p\u003e\u003cp\u003eDuring the nighttime, vertical stratification may lead to gradients in NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e, but the concentration of total oxidants (O\u003csub\u003ex\u003c/sub\u003e = NO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;O\u003csub\u003e3\u003c/sub\u003e) tend to be approximately constant with height. The vertical partitioning of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e may shift due to the emissions(\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), which happens in the surface layer due to anthropogenic and soil emissions of NO\u003csub\u003ex\u003c/sub\u003e, and in the upper mixing layer due to the injection of NO\u003csub\u003ex\u003c/sub\u003e emission sources such as power plants. Generally, in the absence of emission perturbation aloft, the concentrations of NO and NO₂ exhibit a decreasing trend with the increase of altitude, while the concentration of O₃ shows an opposite increasing trend(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Note that the titration reaction of NO and NO\u003csub\u003e3\u003c/sub\u003e is fast, often resulting in low concentrations of NO\u003csub\u003e3\u003c/sub\u003e radicals in the NO\u003csub\u003ex\u003c/sub\u003e source regions, which limits NO\u003csub\u003e3\u003c/sub\u003e oxidation potential in the surface layer, which is common in urban regions (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Nevertheless, NO\u003csub\u003e3\u003c/sub\u003e chemistry may be significantly enhanced in regions with the absence of NO above the surface layer.\u003c/p\u003e\u003cp\u003eTo understand the vertical oxidation at nighttime, a series of vertical field studies of NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e measurements, using advanced platforms like aircraft and tall towers (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), and model simulations were conducted (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). These results revealed a significant altitude dependence of NO\u003csub\u003e3\u003c/sub\u003e, precursors, and scavengers, and found the concentration of NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e is higher aloft than on the ground (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), indicating an active nighttime chemistry aloft. However, due to the limited vertical measurements and datasets, it remains a persistent challenge to evaluate the vertical evolution of NO\u003csub\u003e3\u003c/sub\u003e oxidation over the long term and across diverse environments at the current stage.\u003c/p\u003e\u003cp\u003eHere, we collected a vertical observational dataset of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e from tower that spans different environmental conditions from clean to polluted regions, including Guangzhou, Shenzhen, Beijing in China, and Erie, CO in the U.S., as well as surface NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e dataset globally (Methods). Using PNO\u003csub\u003e3\u003c/sub\u003e as the indicator(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), we characterized the vertical distribution of nocturnal NO\u003csub\u003e3\u003c/sub\u003e radical oxidation capacity and causes. We further built a comprehensive framework to diagnose and evaluate the global trend of vertical NO\u003csub\u003e3\u003c/sub\u003e radical chemistry by using the surface measurement dataset from 2014\u0026ndash;2021, linking it to emission reductions over the past decade.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eCharacterization of enhanced PNO\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e \u003cb\u003ealoft event.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHigher PNO\u003csub\u003e3\u003c/sub\u003e aloft compared with the ground means that the potential of enhanced nocturnal oxidation chemistry in the upper mixing layer, which will cause more air pollutants formation and impact on ground pollution. In order to understand the possibility of enhanced PNO\u003csub\u003e3\u003c/sub\u003e in the upper mixing layer and its characteristics and influencing factors, we classified the observed vertical distribution of PNO\u003csub\u003e3\u003c/sub\u003e into two types. Specifically, the enhanced PNO\u003csub\u003e3\u003c/sub\u003e aloft event (EPE) was defined if the observed PNO\u003csub\u003e3\u003c/sub\u003e at any height (over 20 m, AGL) in the upper mixing layer was greater than 30% of the ground PNO\u003csub\u003e3\u003c/sub\u003e, this threshold exceeds the double uncertainty from the instrument of NO\u003csub\u003ex\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e. The corresponding non-enhanced PNO\u003csub\u003e3\u003c/sub\u003e event (NEPE) was defined when the observed PNO\u003csub\u003e3\u003c/sub\u003e in the upper mixing layer is not significantly higher than near ground, with the ratio of PNO\u003csub\u003e3\u003c/sub\u003e at any layer aloft to the surface lower than 1.3.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea shows the proportion of EPE in the Guangzhou, Beijing, and Shenzhen tower in China reached 72%, 64%, and 68%, respectively, which is much higher than the results in the Erie tower in the United States (16%). Considering that the data from the three sites in China have good seasonal coverage, while the data in the US is only available in winter, we further calculated the proportion of EPE appearing only in winter in China, which still much higher than that in the Erie tower (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In order to further understand the occurrence mechanism of EPE at nighttime, we use the relative concentration of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e on the ground as a standard to simplified the vertical distribution of air masses. We explored all possible vertical distributions of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e based on their relative concentration on the ground (Methods and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When the ground NO\u003csub\u003e2\u003c/sub\u003e \u0026gt; O\u003csub\u003e3\u003c/sub\u003e, we define it as the NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario, and the NO\u003csub\u003ex\u003c/sub\u003e-limited scenario defined as the ground NO\u003csub\u003e2\u003c/sub\u003e \u0026lt; O\u003csub\u003e3\u003c/sub\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea indicates that the probability of EPE in NO\u003csub\u003ex\u003c/sub\u003e-saturated scenarios is much higher than in NO\u003csub\u003ex\u003c/sub\u003e-limited scenarios, with consistent results in Guangzhou, Beijing, and Eric, CO, and the EPE mainly occurs in four specific types of vertical structures (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In Shenzhen, the proportion of EPE in both NO\u003csub\u003ex\u003c/sub\u003e-saturated and NO\u003csub\u003ex\u003c/sub\u003e-limited scenarios is relatively high, and the cause will be discussed later.\u003c/p\u003e\u003cp\u003eThis phenomenon aligns with the theoretical expectations. It is well-known that NO\u003csub\u003ex\u003c/sub\u003e primarily originates from ground-level emissions. Thus, NO\u003csub\u003ex\u003c/sub\u003e concentrations generally decrease with altitude at night, while O\u003csub\u003e3\u003c/sub\u003e concentrations tend to increase with height since it can be less titrated by NO aloft. Under the premise of the relative conservation of the vertical concentration of O\u003csub\u003ex\u003c/sub\u003e since afternoon, if the ground-level NO\u003csub\u003e2\u003c/sub\u003e concentration exceeds that of O\u003csub\u003e3\u003c/sub\u003e, that means the concentrations of NO₂ and O₃ are expected to reach equilibrium inevitably at a particular altitude, and the production rate of nitrate radicals (PNO₃) is anticipated to achieve its maximum value. However, the observed results did not perfectly match theoretical predictions for two main reasons. Firstly, vertical observations are limited to several specific layers, and there may be a lack of observations where PNO\u003csub\u003e3\u003c/sub\u003e peaks occur. Secondly, some occurrences of PNO\u003csub\u003e3\u003c/sub\u003e peak may not have been included in valid results due to the threshold for the enhanced type being set at 30%. If we lower the threshold to 10%, the proportion of the EPE in NO\u003csub\u003ex\u003c/sub\u003e-saturated scenarios across different regions increases, with an average of 86% (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen ground-level NO\u003csub\u003ex\u003c/sub\u003e is lower than O\u003csub\u003e3\u003c/sub\u003e, PNO\u003csub\u003e3\u003c/sub\u003e is theoretically expected to decrease with altitude as NO\u003csub\u003ex\u003c/sub\u003e concentrations decline and O\u003csub\u003e3\u003c/sub\u003e increases. However, O\u003csub\u003ex\u003c/sub\u003e is not always conserved vertically(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). On one hand, the deposition of O\u003csub\u003e3\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e leads to a reduction in ground-level O\u003csub\u003ex\u003c/sub\u003e concentration. On the other hand, differences in the conversion and removal rates of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e at various altitudes may cause actual observations to deviate from theoretical expectations. Additionally, the transportation and injection of NO\u003csub\u003ex\u003c/sub\u003e emissions from elevated NO\u003csub\u003ex\u003c/sub\u003e emission sources or other urban plumes like power plant(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) can lead to a redistribution of NO\u003csub\u003ex\u003c/sub\u003e as well as O\u003csub\u003ex\u003c/sub\u003e in the vertical scale, resulting in increasing NO\u003csub\u003e2\u003c/sub\u003e and thus enhanced nocturnal oxidation chemistry aloft, as frequently observed at the Shenzhen tower(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). However, the occurrence of this phenomenon is highly related to the surroundings and varies depending on the urban environment and emission characteristics. For example, under NO\u003csub\u003ex\u003c/sub\u003e-limited scenarios, the proportion of EPE in Guangzhou, Beijing, and Shenzhen is significantly higher than in Eric (7%), highlighting the considerable impact of high-altitude NO\u003csub\u003ex\u003c/sub\u003e injection from urban human activities on the vertical structure of nighttime atmospheric oxidation.\u003c/p\u003e\u003cp\u003eWe show that the overall median RPNO\u003csub\u003e3\u003c/sub\u003e (the ratio of the maximum PNO\u003csub\u003e3\u003c/sub\u003e value in the upper mixing layer to the ground) in the EPE in the three Chinese megacities sites reached 2.7, means a significant enhancement of PNO\u003csub\u003e3\u003c/sub\u003e over the megacities. Although the EPE occurs under both NO\u003csub\u003ex\u003c/sub\u003e-saturated and NO\u003csub\u003ex\u003c/sub\u003e-limited scenarios, there is a notable difference in the intensity of nighttime chemistry enhancement (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). All sites (except Shenzhen) exhibited significantly higher PNO\u003csub\u003e3\u003c/sub\u003e enhancement under NO\u003csub\u003ex\u003c/sub\u003e-saturated compared to the NO\u003csub\u003ex\u003c/sub\u003e-limited scenarios. Specifically, the median RPNO\u003csub\u003e3\u003c/sub\u003e in Guangzhou, Beijing, and Eric under NO\u003csub\u003ex\u003c/sub\u003e-limited and NO\u003csub\u003ex\u003c/sub\u003e-saturated scenarios were 2.4/3.2, 1.7/2.7, and 1.4/2.9, respectively. Due to the significant impact of high-altitude NO\u003csub\u003ex\u003c/sub\u003e emissions injection, the Shenzhen station (2.0/1.8) showed an inconsistent trend. In addition, the average proportion of RPNO\u003csub\u003e3\u003c/sub\u003e greater than 2 in these four regions can reach 52%, and particularly prominent in Beijing (51%) and Guangzhou (72%), where the sites located in the central of urban agglomerations, higher than the suburban sites of Shenzhen (42%) and Erie, CO (44%). This result highlights the crucial role of NO\u003csub\u003ex\u003c/sub\u003e emissions in regulating EPE events. Under high NO\u003csub\u003ex\u003c/sub\u003e conditions, it is more likely that the chemical activity of NO\u003csub\u003e3\u003c/sub\u003e at high altitudes far exceeds that near the ground.\u003c/p\u003e\u003cp\u003eWe further revealed the pivotal influence of daytime temperature and the boundary layer height on the characteristics of EPE. As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, by taking the Guangzhou tower observation as an example, the higher temperatures at daytime correlate with increasing O\u003csub\u003ex\u003c/sub\u003e levels and a lower nocturnal boundary layer height. High temperatures speed up the photochemistry to produce more oxidants, and higher temperatures during the daytime are typically associated with less cloud, and fast decoupling of the nocturnal boundary layer and residual layer at night (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). These lead to a more pronounced difference in PNO\u003csub\u003e3\u003c/sub\u003e levels within the boundary layer and the residual layer at night. In addition, low nocturnal boundary layer height often implies weaker vertical turbulent mixing and stable atmospheric condition, leading to larger vertical gradients of NO\u003csub\u003ex\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e at the vertical scale, further exacerbating the differences in PNO\u003csub\u003e3\u003c/sub\u003e at the vertical scale(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). When the highest measurement platform at 488 m is also within the nocturnal boundary layer, the vertical variation in PNO\u003csub\u003e3\u003c/sub\u003e concentration is relatively subtle, with a maximum ratio of 2.0 between the elevated and ground-level PNO\u003csub\u003e3\u003c/sub\u003e (at 168 m/surface, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). However, when the nocturnal boundary layer height decreases, for example, drops below 120 m as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, the residual layer PNO\u003csub\u003e3\u003c/sub\u003e concentration can be 2.9 times higher than the near-surface levels and remains consistently higher at 118 m and 168 m. Moreover, due to the limited number of observational points across the entire vertical scale, a refined description of the vertical profile changes is not feasible. At unmonitored heights (e.g., from 168–488 m), higher PNO\u003csub\u003e3\u003c/sub\u003e values may occur, indicating the need for high spatial resolution in vertical measurements of tower systems to fully quantify the depth of the highly reactive zone of NO\u003csub\u003e3\u003c/sub\u003e chemistry at night.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEnvironmental impacts of enhanced PNO\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e \u003cb\u003ealoft event.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe found the proportion of nocturnal ozone concentrations exceeding 10 ppb above 118 m is over 54% and exhibits a rapid upward trend with increasing height (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This indicates that the lifetime of NO is restricted to under 4 minutes, with a rate constant of 1.73×10\u003csup\u003e− 14\u003c/sup\u003e molecule\u003csup\u003e− 1\u003c/sup\u003es\u003csup\u003e− 1\u003c/sup\u003ecm\u003csup\u003e3\u003c/sup\u003e for the NO + O\u003csub\u003e3\u003c/sub\u003e reaction at 298 K. Therefore, the nocturnal residual layer chemistry is minimally affected by the near-surface NO emissions. Using Guangzhou tower as an example, quantitative calculations of O\u003csub\u003ex\u003c/sub\u003e depletion (Methods) at different altitudes reveal the weaker nocturnal O\u003csub\u003ex\u003c/sub\u003e loss at the ground and 488 m levels, compared with the O\u003csub\u003ex\u003c/sub\u003e deficit occurs at 118 m and 168 m (Figure. 3a). This indicates a significant removal process of O\u003csub\u003ex\u003c/sub\u003e occurred in the middle layers, these O\u003csub\u003ex\u003c/sub\u003e may convert to NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e and consumed by the following chemistry, which is in good agreement with the observed distribution of PNO\u003csub\u003e3\u003c/sub\u003e. This smallest O\u003csub\u003ex\u003c/sub\u003e deficit on the surface may be largely due to the less efficient NOx removal via NO\u003csub\u003e3\u003c/sub\u003e chemistry. The vertical O\u003csub\u003ex\u003c/sub\u003e deficit was also confirmed by the results observed at Shenzhen tower and Beijing tower (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, c).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe lifetime is an important index for reflecting the role of NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e chemistry in forming secondary pollutants. Previous work has shown significant differences in NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e lifetimes between urban areas and remote regions(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e–\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Observations from the Guangzhou tower indicate that particulate matter concentration levels remain high at 20–40 µg/m\u003csup\u003e3\u003c/sup\u003e, albeit lower compared to ground levels, as well as the NO\u003csub\u003e3\u003c/sub\u003e-reactive VOC species (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). We estimate that the typical nocturnal lifetimes of NO\u003csub\u003e3\u003c/sub\u003e radicals and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e near the urban surface are short, caused by NO\u003csub\u003e3\u003c/sub\u003e + VOC and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e uptake, at approximately 1–5 minutes and 10–30 minutes, respectively. However, they are two times longer on average in the residual layer due to the lower abundance of NO\u003csub\u003e3\u003c/sub\u003e reactants. This is similar to the case observed in Houston (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), Los Angeles (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), Eastern US(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), London (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), and Seoul (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), but significantly lower than those in remote regions' residual layer (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Therefore, we argue that in areas with particulate matter pollution happens with relative high frequency, the loss of NO\u003csub\u003e3\u003c/sub\u003e in the nocturnal boundary layer and residual layer is still fast to produce secondary pollutants on average, and does not act as a reservoir to a large extent. However, in relatively clean areas, N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e may still act as a reservoir for NO\u003csub\u003ex\u003c/sub\u003e (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the polluted urban areas of China, the chemistry of NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e in the nocturnal residual layer is reactive, and the oxidation of VOCs by NO\u003csub\u003e3\u003c/sub\u003e and the heterogeneous reactions of N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e could significantly contribute to the formation of secondary pollution (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). For example, the contribution of N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e heterogeneous reactions in the residual layer to near-surface nitrate in the Beijing area is important (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Moreover, recent findings have shown that the burst of active chlorine chemistry during the COVID period has significantly enhanced atmospheric oxidation potential and the formation of secondary organic aerosols (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Although synchronous observations are lacking in the residual layer to quantify these contributions, it is anticipated that the formation of nitrate aerosol and active halogen species above the urban residual layer may be like the undisturbed NO-free conditions near the surface(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe simulation results from WRF-CMAQ effectively validate this speculation by taking four Chinese city clusters as an example (Methods). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that the enhancement of PNO\u003csub\u003e3\u003c/sub\u003e aloft compared with the surface at EPE in four city clusters is much higher than those at NEPE condition, which is consistent with the observations in general. In both NO\u003csub\u003ex\u003c/sub\u003e-saturated and limited scenarios, NO\u003csub\u003e3\u003c/sub\u003e chemistry in the upper mixing layer is more active due to reduced influence from NO, thus the ratio of the maximum NO\u003csub\u003e3\u003c/sub\u003e oxidation loss rate (here including NO\u003csub\u003e3\u003c/sub\u003e + VOC and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e uptake) in the upper mixing layer to the ground is greater than 1.0 in four typical Chinese city cluster. It is worth noting that under NO\u003csub\u003ex\u003c/sub\u003e-saturated scenarios, due to the significant enhancement of PNO\u003csub\u003e3\u003c/sub\u003e in the upper mixing layer, the ratio of the maximum NO\u003csub\u003e3\u003c/sub\u003e oxidation loss rate in the upper mixing layer to the ground further increases, especially in BTH and CY regions, the ratio reach up to 14.2 and 20.7, respectively. This further highlight the critical role of EPE on the secondary air pollutants formation above the canopy of urban regions. For the inter-comparison, the vertical loss of NO\u003csub\u003e3\u003c/sub\u003e at night in Eric tower was calculated based on the field observation dataset, and showed a consistent and similar loss pattern as model result presented (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe long-term trend of enhanced PNO\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e \u003cb\u003ealoft event.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWith the ongoing global efforts to reduce and control NO\u003csub\u003ex\u003c/sub\u003e emissions, the proportion of NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario is gradually decreasing. Therefore, the vertical distribution pattern of PNO\u003csub\u003e3\u003c/sub\u003e will systematically shift to the NEPE. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, the long-term observation in the Guangzhou tower confirmed this change with an overall increase in NEPE and decreasing in EPE (from 99–47%) over 2014–2020. Since the long-term vertical measurement of NO\u003csub\u003e3\u003c/sub\u003e precursors is limited globally, and considering that under high NO\u003csub\u003ex\u003c/sub\u003e scenario, the observed proportion of EPE is much higher with a larger enhancement of PNO\u003csub\u003e3\u003c/sub\u003e, thus the fraction of NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario can be representative of the EPE to large extent.\u003c/p\u003e\u003cp\u003eHere we used the fraction of NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario as a proxy for the EPE, and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb shows the average fraction of NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario is much higher in China and India compared with US and EU. This indicates that due to high NO\u003csub\u003ex\u003c/sub\u003e emissions in China and India, the probability of enhanced NO\u003csub\u003e3\u003c/sub\u003e chemistry occurring over urban clusters is higher than that in the United States and Europe. Concerning the four Chinese city clusters, the average fraction of NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario is higher in Peral River Delta (PRD) and the Chengdu-Chongqing area (CY), with both fractions at 46% ± 17%.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec reveals a consistent downward trend in the average proportion of NO\u003csub\u003ex\u003c/sub\u003e-saturated scenarios across the US, EU, and China. Among these regions, China demonstrates the most pronounced reduction, especially within the BTH area of the four city clusters, where a decline rate of 2.6% per year is observed. This trend shows good consistency with the reduction of NO\u003csub\u003ex\u003c/sub\u003e during the past years (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Due to the limited dataset with fewer sites and short time coverage, the trend for India is not further assessed. We should note that even if the trend showed a decrease in NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario with an indicative of the decrease in EPE. The pattern of enhanced PNO\u003csub\u003e3\u003c/sub\u003e aloft still accounts for nearly half of the total in China just like the Guangzhou Canton tower case presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea. In addition, we show that there is a consistently higher fraction of high NO\u003csub\u003ex\u003c/sub\u003e-saturated scenario in urban than non-urban regions, with a faster decrease of the fraction in urban regions (Extended Data Fig.\u0026nbsp;7). Therefore, from a long-term perspective, the EPE would be still important in causing air pollution in urban regions, and this change trigged by NO\u003csub\u003ex\u003c/sub\u003e reduction may have implications for atmospheric chemistry and air quality management on a large scale.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion and implications","content":"\u003cp\u003eIn this study, based on the comprehensive dataset, we reveal a special vertical distribution pattern of nighttime chemical oxidation, clarified the boundary layer dynamic mechanism and the response of vertical differences of nocturnal NO\u003csub\u003e3\u003c/sub\u003e chemistry in the boundary layer on the anthropogenic emissions. The result highlights the large different vertical nocturnal oxidation patterns in high and low NO\u003csub\u003ex\u003c/sub\u003e emission areas. We thus propose a conceptual framework to depict the unique characteristics of NO\u003csub\u003e3\u003c/sub\u003e chemistry and its vertical dependence in varied environments. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, in urban regions with intensive anthropogenic emissions, NO\u003csub\u003e3\u003c/sub\u003e can be rapidly formed by both elevated NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e above the city canopy, and also free from local NO titration. These two aspects provide an ideal environment for NO\u003csub\u003e3\u003c/sub\u003e to react with VOCs and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e uptake with high efficiency, and may cause fast secondary pollutant formation, including nitrate aerosol, secondary organic aerosol, and reactive chlorine precursors that enhance the following daytime photochemistry(\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e–\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). This may contribute to the deterioration of surface air pollution with rapid growth in pollutant concentrations. Importantly, this event happened with very high frequencies in intensive NOx emission regions, highlighting the critical but overlooked role of NO\u003csub\u003e3\u003c/sub\u003e chemistry above these regions. By contrast, PNO\u003csub\u003e3\u003c/sub\u003e is relatively low aloft compared with the ground in rural regions with weak NO\u003csub\u003ex\u003c/sub\u003e emission, and NO titration has a smaller impact on the surface, causing the key area for nighttime oxidation to be at or near the surface, and may be a smaller role aloft. This pattern should be more representative of low anthropogenic emission regions(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe should note that although PNO\u003csub\u003e3\u003c/sub\u003e is a proxy of the nocturnal atmospheric oxidation upper limit, it may overestimate the real atmospheric oxidation capacity in some conditions as indicated by the model results (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In areas with intensive anthropogenic emissions, NO\u003csub\u003e3\u003c/sub\u003e is titrated by NO to form NO\u003csub\u003e2\u003c/sub\u003e rather than effective NOx removal. And NO\u003csub\u003e3\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e may be a reservoir of active nitrogen species rather than an oxidizing agent at low VOC and particulate matter loading regions (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Nevertheless, the aim of this study was not to accurately quantify nocturnal atmospheric oxidation, but to systematically assess the vertical pattern and evolution of the nocturnal oxidation. Finally, we highlight that more detailed, comprehensive field experiments and model simulations with more refined spatial resolution are needed, to identify the role of nighttime chemistry in the upper layer and residual layer on the surface air pollution in high NO\u003csub\u003ex\u003c/sub\u003e urban regions. Better understanding of residual layer chemistry holds potential to improve strategies for regional air quality mitigation as well as the air pollution forecast.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eVertical observation dataset\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe obtained vertical observation datasets (NO\u003csub\u003e2\u003c/sub\u003e, O\u003csub\u003e3\u003c/sub\u003e, and temperature) from four in different regions in different regions, including Guangzhou, Shenzhen, Beijing in China, and Erie, CO in the U.S. The vertical observation datasets from Guangzhou, Shenzhen, and Beijing tower were fixed-point at three to four heights, and the tower in Eric, CO was continuous vertically. The datasets from different towers span different periods, ranging from 2011 to 2022. Vertical observations were conducted within 500 m and time resolution was 1 hour. Detailed descriptions of the vertical observations are listed in Supplementary Text 1 and Extended Data Table\u0026nbsp;1.\u003c/p\u003e\u003cp\u003eTo eliminate observational outliers and ensure complete vertical observational data at the same time, we excluded profiles based on the following criteria, referring to previous literature(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e concentrations were less than 0 ppbv or greater than 500 ppbv. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) For Guangzhou Shenzhen, and Beijing tower, which have only several vertical levels, a profile with missing NO\u003csub\u003e2\u003c/sub\u003e or O\u003csub\u003e3\u003c/sub\u003e data at any level was excluded. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) For the tower in Eric, CO, where continuous vertical observations were conducted, data was initially averaged every 20 m; The profile was excluded if there were missing NO\u003csub\u003e2\u003c/sub\u003e or O\u003csub\u003e3\u003c/sub\u003e values after averaging(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGround observation dataset\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe hourly observational data of ground-level NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e at 2024 stations in China were obtained from the China National Environmental Monitoring Center network. Concurrently, data for the United States and the European Union were collected from the Environmental Protection Agency Air Quality System monitoring, including 469 and 2643 stations, respectively. In addition, data for India at 267 stations are available from the Central Control Room for Air Quality Management. The time range is from 2014 to 2021.\u003c/p\u003e\u003cp\u003eTo ensure the reliability of ground observation data, we excluded data based on the following criteria (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The values less than 0 ppbv or greater than 500 ppbv. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The hourly standardization (calculated as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{z}_{i}=\\frac{{x}_{i}-\\stackrel{-}{x}}{\\sigma\\:}\\)\u003c/span\u003e\u003c/span\u003e, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{x}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the hourly data, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{x}\\)\u003c/span\u003e\u003c/span\u003e represents the monthly mean, σ is the standard deviation of each month) value exceeding 5. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Showing minimal daily variation (the difference between the maximum and minimum values within a day is less than 2 ppbv). (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) At least 4 out of 5 consecutive hours have the same value. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Unrealistically large peaks are observed in the time series. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) The effective hours at night (20:00–04:00) are less than less than 75% (6 h), effective days are less than 60% (18 d) per month (30 d), and effective days are less than 60% (219 d) per year. These criteria removed 2.9%, 17.7%, 24.7%, and 41.9% of the hourly data in China, the European Union, the United States, and India, respectively.\u003c/p\u003e\u003cp\u003eAccording to the rules provided by the Tropospheric Ozone Assessment Report (TOAR), sites are categorized as urban, suburban, and rural based on three parameters (population density, nighttime lights, and NO\u003csub\u003e2\u003c/sub\u003e column) (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). The categorization criteria are as follows: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Urban sites are characterized by population densities exceeding 1000 people km\u003csup\u003e− 2\u003c/sup\u003e, nighttime lights greater than 60, and nighttime lights with 25 km radius of the monitoring site equal 63. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Suburban sites exhibit population densities ranging from 200 to 1000 people km\u003csup\u003e− 2\u003c/sup\u003e, nighttime lights below 60, and nighttime light within a 5 km radius of the monitoring site exceeding 25. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Rural sites have population densities equal to or less than 200 people km\u003csup\u003e− 2\u003c/sup\u003e, nighttime lights within a 5 km radius of the monitoring site below 25, and NO\u003csub\u003e2\u003c/sub\u003e column densities less than 8x10\u003csup\u003e15\u003c/sup\u003e molecules cm\u003csup\u003e− 2\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReanalysis dataset\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe used the boundary layer height from the fifth-generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis dataset of the global climate (ERA5). This dataset is generated through the assimilation of model data with various observations such as radiosonde and satellite data. ERA5 dataset provides comprehensive coverage on a global scale, featuring a horizontal resolution of 0.25° x 0.25°, a temporal resolution of 1 hour, and a vertical resolution comprising 37 standard pressure layers. For our study, we selected the Planetary Boundary Layer Height (PBLH) data for January, April, July, and October from 2014 to 2020 for analysis of the Guangzhou tower.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEnumerating all vertical patterns of NO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eand O\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e \u003cb\u003ebased on ground relative concentration.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAccording to the relative concentrations of ground-level NO\u003csub\u003e2\u003c/sub\u003e (gNO\u003csub\u003e2\u003c/sub\u003e) and O\u003csub\u003e3\u003c/sub\u003e (gO\u003csub\u003e3\u003c/sub\u003e), two scenarios can be distinguished: one where the gNO\u003csub\u003e2\u003c/sub\u003e \u0026lt; gO\u003csub\u003e3\u003c/sub\u003e, and another where the gNO\u003csub\u003e2\u003c/sub\u003e \u0026gt; gO\u003csub\u003e3\u003c/sub\u003e. On this basis, there are multiple vertical distribution patterns for NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e, which are mainly influenced by their vertical distribution and the relative concentration at high altitudes (hNO\u003csub\u003e2\u003c/sub\u003e and hO\u003csub\u003e3\u003c/sub\u003e). Therefore, based on the three classification criteria, we use an exhaustive approach to list all possible vertical distribution patterns of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e (Extended Data Table\u0026nbsp;2). Firstly, according to the relative concentrations of gNO\u003csub\u003e2\u003c/sub\u003e and gO\u003csub\u003e3\u003c/sub\u003e, they can be divided into two categories: gNO\u003csub\u003e2\u003c/sub\u003e \u0026lt; gO\u003csub\u003e3\u003c/sub\u003e and gNO\u003csub\u003e2\u003c/sub\u003e \u0026gt; gO\u003csub\u003e3\u003c/sub\u003e. Then, further classification is carried out based on the vertical distribution of O\u003csub\u003e3\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e concentrations. In general, the concentration of NO\u003csub\u003e2\u003c/sub\u003e decreases with height, while the concentration of O\u003csub\u003e3\u003c/sub\u003e increases with height. However, in certain special cases, their vertical distributions may change. For instance, when the upper atmosphere is affected by transportation of NO\u003csub\u003ex\u003c/sub\u003e emissions, NO\u003csub\u003e2\u003c/sub\u003e may show an increasing distribution with height, while O\u003csub\u003e3\u003c/sub\u003e may exhibit a decreasing distribution. Additionally, dry deposition can also influence the vertical distribution of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e. Therefore, both O\u003csub\u003e3\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e concentrations can either increase or decrease with altitude. When O\u003csub\u003e3\u003c/sub\u003e concentration increases with height, it means that the concentration of O\u003csub\u003e3\u003c/sub\u003e at high altitude is greater than that at ground level (hO\u003csub\u003e3\u003c/sub\u003e \u0026gt; gO\u003csub\u003e3\u003c/sub\u003e), NO\u003csub\u003e2\u003c/sub\u003e concentration may either increase (hNO\u003csub\u003e2\u003c/sub\u003e \u0026gt; gNO\u003csub\u003e2\u003c/sub\u003e) or decrease (hNO\u003csub\u003e2\u003c/sub\u003e \u0026lt; gNO\u003csub\u003e2\u003c/sub\u003e) with height. Conversely, when O\u003csub\u003e3\u003c/sub\u003e concentration decreases with height (hO\u003csub\u003e3\u003c/sub\u003e \u0026lt; gO\u003csub\u003e3\u003c/sub\u003e), NO\u003csub\u003e2\u003c/sub\u003e concentration can also either increase or decrease with height. Furthermore, the relative concentration of gNO\u003csub\u003e2\u003c/sub\u003e and gO\u003csub\u003e3\u003c/sub\u003e, as well as their vertical distribution, will affect the relative concentration of high-level NO\u003csub\u003e2\u003c/sub\u003e (hNO\u003csub\u003e2\u003c/sub\u003e) and O\u003csub\u003e3\u003c/sub\u003e (hO\u003csub\u003e3\u003c/sub\u003e). Therefore, we further classify into two categories based on the relative concentration of hNO\u003csub\u003e2\u003c/sub\u003e and hO\u003csub\u003e3\u003c/sub\u003e: hNO\u003csub\u003e2\u003c/sub\u003e \u0026gt; hO\u003csub\u003e3\u003c/sub\u003e and hNO\u003csub\u003e2\u003c/sub\u003e \u0026lt; hO\u003csub\u003e3\u003c/sub\u003e. Overall, according to the above classification criteria, there are 14 possible vertical distribution patterns for NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e, which account for 99.7%, 94.8%, 99.7%, and 100% of the observed data in Guangzhou, Shenzhen, Beijing, and Eric and CO, respectively. However, some special cases are not included, where the concentrations of NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e are equal at ground-level or at high-level, or where NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e remains unchanged in the vertical direction. Due to their rarity, these cases are not considered in this study.\u003c/p\u003e\u003cp\u003eThen we categorize all observation data based on the ground-level and highest observation altitude NO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e3\u003c/sub\u003e concentrations (gNO\u003csub\u003e2\u003c/sub\u003e, gO\u003csub\u003e3\u003c/sub\u003e, hNO\u003csub\u003e2\u003c/sub\u003e, and hO\u003csub\u003e3\u003c/sub\u003e), and calculate the occurrence probability of the enhanced PNO\u003csub\u003e3\u003c/sub\u003e aloft event (EPE) for each category. It is worth noting that for some cases where EPE did not occur, we believe the reason may be that the peak of PNO\u003csub\u003e3\u003c/sub\u003e did not appear at the maximum observation height. Therefore, when EPE occurs at moderate heights, we will also consider it as an EPE in this category.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe definition of O\u003c/b\u003e\u003csub\u003e\u003cb\u003ex\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eresidual capacity.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe residual capacity of nighttime O\u003csub\u003ex\u003c/sub\u003e at different heights is defined as the ratio of the average concentration of O\u003csub\u003ex\u003c/sub\u003e at nighttime (20:00–04:00 LT) to the average concentration of O\u003csub\u003ex\u003c/sub\u003e in the afternoon (14:00–17:00 LT). Due to the concentration of O\u003csub\u003ex\u003c/sub\u003e reaches is daily peak between 14:00–17:00 and the vertical mixing will be strongest(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eWRF-CMAQ\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCMAQ version 5.2 was employed to simulate air quality across China, with a horizontal resolution of 36 km and 18 vertical layers. The SAPRC07 mechanism was used for gas-phase chemistry, alongside the Aero6 module for aerosol processes(\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). The simulation period spanned from September 26 to November 3, 2019, with three spin-up days. Meteorological fields were generated using WRF version 4.2, driven by NCEP FNL reanalysis data at 0.25° × 0.25° resolution. Anthropogenic emissions were obtained from the Multi-resolution Emission Inventory for China (MEIC v1.3, available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.meicmodel.org\u003c/span\u003e\u003cspan address=\"http://www.meicmodel.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, last access: 17 June 2024) (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e), while biogenic emissions were estimated using MEGAN version 2.1(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Emissions from open biomass burning were derived from the FINN database (FINNv1.5; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www2.acom.ucar.edu/modeling/finn-fire-inventory-ncar\u003c/span\u003e\u003cspan address=\"https://www2.acom.ucar.edu/modeling/finn-fire-inventory-ncar\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, last access: 17 June 2024) (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Integrated Reaction Rate (IRR) module in CMAQ was used to quantify the contributions of different chemical processes to the radical budget (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). This tool calculated the real-time production rates of radicals through various chemical pathways, helping assess their roles in pollutant formation. Extended Data Table\u0026nbsp;3 lists the NO\u003csub\u003e3\u003c/sub\u003e-involved gas-phase reactions in CMAQ.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe source data generated in this study have been deposited in the figshare repository under accession code XXX. The data of the measurements in this study could be obtained upon request by the corresponding author ([email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main figures are produced by Python. The code for the model simulation can be obtained from the figshare repository under accession code XXX.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.C.W. received financial support from the National Key Research and Development Program of China (2023YFC3710900), the Guangdong Natural Science Funds for Distinguished Young Scholar (2024B1515020075). K.L. received financial support from the National Natural Science Foundation of China (grants 22325601, 22325201, 22221004), the National Research Program for Key Issue in Air Pollution Control (grant 2023YFC3706100).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK.D.L., H.C.W., S.J.F., and S.S.B. conceived the study. Y.J.Q., and H.C.W. analyzed the data and wrote the manuscript with inputs from X.R.C., X.L., Y.M.L., Z.B.S., B.Y., Y.J.T. and Y.H.Z. C.L.P. and L.L. provide the vertical dataset. M.M.Q. provided the CMAQ model simulation result. All authors contributed to the discussed results and commented on the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Statement.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests. \u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eS. S. Brown, J. Stutz, Nighttime radical observations and chemistry. \u003cem\u003eChemical Society Reviews\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 6405-6447 (2012).\u003c/li\u003e\n\u003cli\u003eN. L. Ng\u003cem\u003e et al.\u003c/em\u003e, Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol. \u003cem\u003eAtmos. Chem. Phys.\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 2103-2162 (2017).\u003c/li\u003e\n\u003cli\u003eJ. K. 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Phys.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 12629-12646 (2022).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7100046/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7100046/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNitrate radicals (NO\u003csub\u003e3\u003c/sub\u003e) play a crucial role in the removal of nitrogen oxides (NO\u003csub\u003ex\u003c/sub\u003e) from Earth's atmosphere and act as the dominant nocturnal oxidant in polluted regions, thereby influencing air quality, climate, and ecological systems. However, the vertical variations of NO\u003csub\u003e3\u003c/sub\u003e chemistry within the planetary boundary layer during nighttime remain poorly understood due to the stratification of nocturnal air masses and complex chemical conditions. Here, we present vertical and ground-based observations of NO\u003csub\u003e3\u003c/sub\u003e precursors across diverse atmospheric environments. Our results indicate that the enhanced NO\u003csub\u003e3\u003c/sub\u003e chemistry aloft event, defined as the NO\u003csub\u003e3\u003c/sub\u003e production rate above the canopy being higher than at surface levels, occurs frequently in megacities (64-72%) with a median enhancement factor of 2.7. This phenomenon likely largely promotes more rapid oxidation reactions and secondary pollutant formation in the aloft environment. We show this event is more prevalent in China and India than in the United States and Europe. However, a rapid decline in its frequency has been observed in China in recent years, closely linked to the implementation of stringent NO\u003csub\u003ex\u003c/sub\u003e emission control measures. We demonstrate that this event is attributed to the interplay between intense ground-level NOx emissions and atmospheric stability. These findings highlight the critical role of vertical gradients in nocturnal NO\u003csub\u003e3\u003c/sub\u003e chemistry on surface air pollution and underscore the need for comprehensive vertical measurement to support further improvement of urban air quality.\u003c/p\u003e","manuscriptTitle":"Anthropogenic emission largely enhances nocturnal oxidation chemistry in the upper mixing layer of megacities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 11:24:41","doi":"10.21203/rs.3.rs-7100046/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"875daa7e-8dd3-4b4f-9e40-a2e9fa87aa7c","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":52126696,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry/Atmospheric chemistry"},{"id":52126697,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"}],"tags":[],"updatedAt":"2025-07-29T11:24:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-29 11:24:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7100046","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7100046","identity":"rs-7100046","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}