Persistent Heavy Winter Nitrate Pollution Driven by Increased Photochemical Oxidants in Northern China

Impact of Molecular Chlorine Production from Aerosol Iron Photochemistry on Atmospheric Oxidative Capacity in North China

Elevated levels of atmospheric molecular chlorine (Cl2) have been observed during the daytime in recent field studies in China but could not be explained by the current chlorine chemistry mechanisms in models. Here, we propose a Cl2 formation mechanism initiated by aerosol iron photochemistry to explain daytime Cl2 formation. We implement this mechanism into the GEOS-Chem chemical transport model and investigate its impacts on the atmospheric composition in wintertime North China where high levels of Cl2 as well as aerosol chloride and iron were observed. The new mechanism accounts for more than 90% of surface air Cl2 production in North China and consequently increases the surface air Cl2 abundances by an order of magnitude, improving the model's agreement with observed Cl2. The presence of high Cl2 significantly alters the oxidative capacity of the atmosphere, with a factor of 20-40 increase in the chlorine radical concentration and a 20-40% increase in the hydroxyl radical concentration in regions with high aerosol chloride and iron loadings. This results in an increase in surface air ozone by about 10%. This new Cl2 formation mechanism will improve the model simulation capability for reactive chlorine abundances in the regions with high emissions of chlorine and iron.

Response of PM2.5 chemical composition to the emission reduction and meteorological variation during the COVID-19 lockdown

PM2.5 is a main atmospheric pollutant with various sources and complex chemical compositions, which are influenced by various factors, such as anthropogenic emissions (AE) and meteorological conditions (MC). MC have a significant impacts on variations in atmospheric pollutant; therefore, emission reduction policies and ambient air quality are non-linearly correlated, which hinders the accurate assessment of the effectiveness of control measures. In this study, we conducted online observations of PM2.5 and its chemical composition in Hohhot, China, from December 1, 2019, to February 29, 2020, to investigate how the chemical compositions of PM2.5 respond to the variations in AE and MC. Moreover, the random forest (RF) model was used to quantify the contributions of AE and MC to PM2.5 and its chemical composition during severe hazes and the COVID-19 pandemic lockdown period. During the clean period, MC reduced PM2.5 concentrations by 124%, while MC incresed PM2.5 concentrations by 49% during severe pollution episode. Inorganic aerosols (SO42-, NO3-, and NH4+) showed the strongest response to MC. MC significantly contributed to PM2.5 (36%), SO42- (32%), NO3- (29%), NH4+ (28%), OC (22%), and SOC (17%) levels during pollution episodes. From the pre-lockdown to lockdown period, AE (MC) contributed 52% (48%), 81% (19%), 48% (52%), 68% (32%), 59% (41%), and 288% (-188%) to the PM2.5, SO42-, NO3-, NH4+, OC, and SOC reductions, respectively. The variations in MC (especially the increase in relative humidity) rapidly generated meteorologically sensitive species (SO42-, NO3-, and NH4+), which led to severe winter pollution. This study provides a reference for assessing the net benefits of emission reduction measures for PM2.5 and its chemical compositions.

Compositions and sources of fluorescent water-soluble and water-insoluble organic aerosols

Brown carbon (BrC), the light-absorbing component of organic aerosols, plays a significant role in climate change and atmospheric photochemistry. However, the water-insoluble fractions of BrC have not been extensively studied, limiting the assessment of the overall climate effects of BrC. In this study, water-soluble and -insoluble organic carbon (i.e., WSOC and WIOC) in wintertime aerosols in Hefei were subsequently fractionated, and their fluorescence properties were comparatively investigated with the excitation-emission matrix method. WIOC contributing 57.1 % was the major component of organic carbon. WSOC with the largest contribution from humic-like regions exhibited a redshift compared to WIOC. Three humic-like substances (HULIS) with different oxidation degrees and one protein-like substances (PRLIS) were identified as the major fluorescent components by the parallel factor analysis. WSOC had more highly oxygenated HULIS, whereas low-oxygenated HULIS dominated WIOC. Nighttime WIOC contained more less-oxygenated species. The positive matrix factorization analysis suggested that biomass burning (43 %) was the largest source of both fluorescent WSOC and WIOC. Coal combustion contributed much more to fluorescent WIOC (40 %), whereas secondary formation contributed more to fluorescent WSOC (12 %). During aerosol pollution episodes, the increase in fluorescence efficiency was much greater for WIOC (25 %) than for WSOC (12 %), and WSOC and WIOC experienced a redshift and blueshift in emission wavelength, respectively. WSOC had more highly oxygenated HULIS, while WIOC had more less-oxygenated HULIS in aerosol episodes than the non-episodic periods. In addition, aerosol pollution was accompanied by the increased contributions of biomass burning and coal combustion to both fluorescent WSOC and WIOC, while the decreased relative contribution of secondary formation to fluorescent WSOC. Our findings highlighted the different fluorescence properties, compositions and sources of fluorescent WSOC and WIOC, providing a comprehensive view of BrC aerosols.

Radical chemistry and VOCs-NOx-O3-nitrate sensitivity in the polluted atmosphere of a suburban site in the North China Plain

In this study, the chemical mechanisms of O3 and nitrate formation as well as the control strategy were investigated based on extensive observations in Tai'an city in the NCP and an observation-constrained box model. The results showed that O3 pollution was severe with the maximum hourly O3 concentration reaching 150 ppb. Higher O3 concentration was typically accompanied by higher PM2.5 concentrations, which could be ascribed to the common precursors of VOCs and NOx. The modeled averaged peak concentrations of OH, HO2, and RO2 were relatively higher compared to previous observations, indicating strong atmospheric oxidation capacity in the study area. The ROx production rate increased from 2.8 ppb h-1 to 5 ppb h-1 from the clean case to the heavily polluted case and was dominated by HONO photolysis, followed by HCHO photolysis. The contribution of radical-self combination to radical termination gradually exceeded NO2 + OH from clean to polluted cases, indicating that O3 formation shifted to a more NOx-limited regime. The O3 production rate increased from 14 ppb h-1 to 22 ppb h-1 from clean to heavily polluted cases. The relative incremental reactivity (RIR) results showed that VOCs and NOx had comparable RIR values during most days, which suggested that decreasing VOCs or NOx was both effective in alleviating O3 pollution. In addition, HCHO, with the largest RIR value, made important contribution to O3 production. The Empirical Kinetic Modeling Approach (EKMA) revealed that synergistic control of O3 and nitrate can be achieved by decreasing both NOx and VOCs emissions (e.g., alkenes) with the ratio of 3:1. This study emphasized the importance of NOx abatement for the synergistic control of O3 and nitrate pollution in the Tai'an area as the sustained emissions control has shifted the O3 and nitrate formation to a more NOx-limited regime.

Identifying Driving Factors of Atmospheric N2O5 with Machine Learning

Dinitrogen pentoxide (N2O5) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of N2O5 formation remains challenging using traditional statistical methods, impeding effective emission control measures to mitigate NOx-induced air pollution. Here, we adopted machine learning assisted by steady-state analysis to elucidate the driving factors of N2O5 before and during the 2022 Winter Olympics (WO) in Beijing. Higher N2O5 concentrations were observed during the WO period compared to the Pre-Winter-Olympics (Pre-WO) period. The machine learning model accurately reproduced ambient N2O5 concentrations and showed that ozone (O3), nitrogen dioxide (NO2), and relative humidity (RH) were the most important driving factors of N2O5. Compared to the Pre-WO period, the variation in trace gases (i.e., NO2 and O3) along with the reduced N2O5 uptake coefficient was the main reason for higher N2O5 levels during the WO period. By predicting N2O5 under various control scenarios of NOx and calculating the nitrate formation potential from N2O5 uptake, we found that the progressive reduction of nitrogen oxides initially increases the nitrate formation potential before further decreasing it. The threshold of NOx was approximately 13 ppbv, below which NOx reduction effectively reduced the level of night-time nitrate formations. These results demonstrate the capacity of machine learning to provide insights into understanding atmospheric nitrogen chemistry and highlight the necessity of more stringent emission control of NOx to mitigate haze pollution.

Nitrate formation mechanisms causing high concentration of PM2.5 in a residential city with low anthropogenic emissions during cold season

During the cold season in South Korea, NO3- concentrations are known to significantly increase, often causing PM2.5 to exceed air quality standards. This study investigated the formation mechanisms of NO3- in a suburban area with low anthropogenic emissions. The average PM2.5 was 25.3 μg m-3, with NO3- identified as the largest contributor. Ammonium-rich conditions prevailed throughout the study period, coupled with low atmospheric temperature facilitating the transfer of gaseous HNO3 into the particulate phase. This result indicates that the formation of HNO3 played a crucial role in determining particulate NO3- concentration. Nocturnal increases in NO3- were observed alongside increasing ozone (O3) and relative humidity (RH), emphasizing the significance of heterogeneous reactions involving N2O5. NO3- concentrations at the study site were notably higher than in Seoul, the upwind metropolitan area, during a high concentration episode. This difference could potentially attributed to lower local NO concentrations, which enhanced the reaction between O3 and NO2, to produce NO3 radicals. High concentrations of Cl- and dust were also identified as contributors to the elevated NO3- concentrations.

Quantifying the contributions of meteorology, emissions, and transport to ground-level ozone in the Pearl River Delta, China

Ozone pollution presents a growing air quality threat in urban agglomerations in China. It remains challenge to distinguish the roles of emissions of precursors, chemical production and transportations in shaping the ground-level ozone trends, largely due to complicated interactions among these 3 major processes. This study elucidates the formation factors of ozone pollution and categorizes them into local emissions (anthropogenic and biogenic emissions), transport (precursor transport and direct transport from various regions), and meteorology. Particularly, we attribute meteorology, which affects biogenic emissions and chemical formation as well as transportation, to a perturbation term with fluctuating ranges. The Community Multiscale Air Quality (CMAQ) model was utilized to implement this framework, using the Pearl River Delta region as a case study, to simulate a severe ozone pollution episode in autumn 2019 that affected the entire country. Our findings demonstrate that the average impact of meteorological conditions changed consistently with the variation of ozone pollution levels, indicating that meteorological conditions can exert significant control over the degree of ozone pollution. As the maximum daily 8-hour average (MDA8) ozone concentrations increased from 20 % below to 30 % above the National Ambient Air Quality Standard II, contributions from emissions and precursor transport were enhanced. Concurrently, direct transport within Guangdong province rose from 13.8 % to 22.7 %, underscoring the importance of regional joint prevention and control measures under adverse weather conditions. Regarding biogenic emissions and precursor transport that cannot be directly controlled, we found that their contributions were generally greater in urban areas with high nitrogen oxides (NOx) levels, primarily due to the stronger atmospheric oxidation capacity facilitating ozone formation. Our results indicate that not only local anthropogenic emissions can be controlled in urban areas, but also the impacts of local biogenic emissions and precursor transport can be potentially regulated through reducing atmospheric oxidation capacity.

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

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

Characterizing the emission trends and pollution evolution patterns during the transition period following COVID-19 at an industrial megacity of central China

After the resumption of work and production following the COVID-19 pandemic, many cities entered a "transition phase", characterized by the gradual recovery of emission levels from various sources. Although the overall PM2.5 emission trends have recovered, the specific changes in different sources of PM2.5 remain unclear. Here, we investigated the changes in source contributions and the evolution pattern of pollution episodes (PE) in Wuhan during the "transition period" and compared them with the same period during the COVID-19 lockdown. We found that vehicle emissions, industrial processes, and road dust exhibited significant recoveries during the transition period, increasing by 5.4%, 4.8%, and 3.9%, respectively, during the PE. As primary emissions increased, secondary formation slightly declined, but it still played a predominant role (accounting for 39.1∼ 43.0% of secondary nitrate). The reduction in industrial activities was partially offset by residential burning. The evolution characteristics of PE exhibited significant differences between the two periods, with PM2.5 concentration persisting at a high level during the transition period. The differences in the evolution patterns of the two periods were also reflected in their change rates at each stage, which mostly depend on the pre-PE concentration level. The transition period shows a significantly higher value (8.4 μg m-3 h-1) compared with the lockdown period, almost double the amount. In addition to local emissions, regional transport should be a key consideration in pollution mitigation strategies, especially in areas adjacent to Wuhan. Our study quantifies the variations in sources between the two periods, providing valuable insights for optimizing environmental planning to achieve established goals.

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

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

Rapid hydrolysis of NO2 at High Ionic Strengths of Deliquesced Aerosol Particles

Nitrogen dioxide (NO2) hydrolysis in deliquesced aerosol particles forms nitrous acid and nitrate and thus impacts air quality, climate, and the nitrogen cycle. Traditionally, it is considered to proceed far too slowly in the atmosphere. However, the significance of this process is highly uncertain because kinetic studies have only been made in dilute aqueous solutions but not under high ionic strength conditions of the aerosol particles. Here, we use laboratory experiments, air quality models, and field measurements to examine the effect of the ionic strength on the reaction kinetics of NO2 hydrolysis. We find that high ionic strengths (I) enhance the reaction rate constants (kI) by more than an order of magnitude compared to that at infinite dilution (kI=0), yielding log10(kI/kI=0) = 0.04I or rate enhancement factor = 100.04I. A state-of-the-art air quality model shows that the enhanced NO2 hydrolysis reduces the negative bias in the simulated concentrations of nitrous acid by 28% on average when compared to field observations over the North China Plain. Rapid NO2 hydrolysis also enhances the levels of nitrous acid in other polluted regions such as North India and further promotes atmospheric oxidation capacity. This study highlights the need to evaluate various reaction kinetics of atmospheric aerosols with high ionic strengths.

Knowledge-guided machine learning reveals pivotal drivers for gas-to-particle conversion of atmospheric nitrate

Particulate nitrate, a key component of fine particles, forms through the intricate gas-to-particle conversion process. This process is regulated by the gas-to-particle conversion coefficient of nitrate (ε(NO3-)). The mechanism between ε(NO3-) and its drivers is highly complex and nonlinear, and can be characterized by machine learning methods. However, conventional machine learning often yields results that lack clear physical meaning and may even contradict established physical/chemical mechanisms due to the influence of ambient factors. It urgently needs an alternative approach that possesses transparent physical interpretations and provides deeper insights into the impact of ε(NO3-). Here we introduce a supervised machine learning approach-the multilevel nested random forest guided by theory approaches. Our approach robustly identifies NH4+, SO42-, and temperature as pivotal drivers for ε(NO3-). Notably, substantial disparities exist between the outcomes of traditional random forest analysis and the anticipated actual results. Furthermore, our approach underscores the significance of NH4+ during both daytime (30%) and nighttime (40%) periods, while appropriately downplaying the influence of some less relevant drivers in comparison to conventional random forest analysis. This research underscores the transformative potential of integrating domain knowledge with machine learning in atmospheric studies.

When and why PM2.5 is high in Seoul, South Korea: Interpreting long-term (2015-2021) ground observations using machine learning and a chemical transport model

Seoul has high PM2.5 concentrations and has not attained the national annual average standard so far. To understand the reasons, we analyzed long-term (2015-2021) hourly observations of aerosols (PM2.5, NO3-, NH4+, SO42-, OC, and EC) and gases (CO, NO2, and SO2) from Seoul and Baekryeong Island, a background site in the upwind region of Seoul. We applied the weather normalization method for meteorological conditions and a 3-dimensional chemical transport model, GEOS-Chem, to identify the effect of policy implementation and aerosol formation mechanisms. The monthly mean PM2.5 ranges between about 20 μg m-3 (warm season) and about 40 μg m-3 (cold season) at both sites, but the annual decreasing rates were larger at Seoul than at Baengnyeong (-0.7 μg m-3 a-1 vs. -1.8 μg m-3 a-1) demonstrating the effectiveness of the local air quality policies including the Special Act on Air Quality in the Seoul Metropolitan Area (SAAQ-SMA) and the seasonal control measures. The weather-normalized monthly mean data shows the highest PM2.5 concentration in March and the lowest concentration in August throughout the 7 years with NO3- accounting for about 40 % of the difference between the two months at both sites. Taking together with the GEOS-Chem model results, which reproduced the elevated NO3- in March, we concluded the elevated atmospheric oxidant level increases in HNO3 (which is not available from the observation) and the still low temperatures in March promote rapid production of NO3-. We used Ox (≡ O3 + NO2) from the observation and OH from the GEOS-Chem as a proxy for the atmospheric oxidant level which can be a source of uncertainty. Thus, direct observations of OH and HNO3 are needed to provide convincing evidence. This study shows that reducing HNO3 levels through atmospheric oxidant level control in the cold season can be effective in PM2.5 mitigation in Seoul.

Trends and drivers of aerosol vertical distribution over China from 2013 to 2020: Insights from integrated observations and modeling

Understanding aerosol vertical distribution is of great importance to climate change and atmospheric chemistry, but there is a dearth of systematical analysis for aerosol vertical distribution amid rapid emission decline after 2013 in China. Here, the GEOS-Chem model and multiple-sourced observations were applied to quantify the changes of aerosol vertical distributions in response to clean air actions. In 2013-2020, the MODIS aerosol optical depth (AOD) presented extensive decreasing trends by -7.9 %/yr to -4.2 %/yr in summer and -6.1 %/yr to -5.8 %/yr in winter in polluted regions. Vertically, the aerosol extinction coefficient (AEC) from CALIPSO decreased by -8.0 %/yr to -5.5 %/yr below ~1 km, but the trends weakened significantly with increasing altitude. Compared with available measurements, the model can reasonably reproduce 2013-2020 trends and seasonality in AOD and vertical AEC. Model simulations confirm that emission reduction was the dominant driver of the 2013-2020 decline in AOD, while the effect of meteorology varied seasonally, with contributions ranging from -2 % to 13 % in summer and -67 % to -2 % in winter. Vertical distributions of emission-driven AEC trends strongly depended on emission reductions, local planetary boundary layer height, and relative humidity. For aerosol components, sulfate accounted for ~50 % of the AOD decline during summer, followed by ammonium and organic aerosol, while in winter the contribution of organic aerosol doubled (24 %-35 %), and nitrate exhibited a weak increasing trend. Chemical production and meteorological conditions (e.g., relative humidity) primarily drove the nitrate contribution, but emission reduction and hygroscopicity were decisive for other components. This work provides an integrated observational and modeling effort to better understand rapid changes in aerosol vertical distribution over China.

Influence of atmospheric oxidation capacity on atmospheric particulate matters concentration in Lanzhou

The atmospheric oxidation capacity (AOC) reflects the removal rate of atmospheric pollutants, and this index is typically characterized by the oxidant concentration or total reaction rate. The AOC plays a crucial role in the formation of atmospheric particulate matters and serves as an important indicator for studying changes in the concentration. In this study, we analyse the characteristics of atmospheric oxidants in Lanzhou based on data in the year of 2020 and 2021 retrieved from the Atmospheric Comprehensive Observation Station in Lanzhou. Empirical equations are applied to estimate the impact of atmospheric oxidative properties secondary generation concentrations of atmospheric particulate matters with different particle sizes. The results indicate that the annual average values of Ox were 146 μg/m3 in 2020 and 139 μg/m3 in 2021. The AOC was the highest in summer and lowest in winter. The correlation coefficient between O3 and Ox was significantly higher than that between NO2 and Ox, suggesting that O3 exerted a greater impact on the AOC in Lanzhou. A low AOC (MDA8 O3 ≤ 100 μg/m3) promoted the oxidation process of VOCs and other precursors, leading to the generation of secondary aerosols and subsequent formation of secondary particles. There were negative correlations between Ox and atmospheric particulate matters, secondary inorganic components, sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), indicating that excessively high levels of Ox could inhibit the conversion rate of SO2 and NO2 into their respective forms to a certain extent.

Dominant physical and chemical processes impacting nitrate in Shandong of the North China Plain during winter haze events

Nitrate has been a dominant component of PM2.5 since the stringent emission control measures implemented in China in 2013. Clarifying key physical and chemical processes influencing nitrate concentrations is crucial for eradicating heavy air pollution in China. In this study, we explored dominant processes impacting nitrate concentrations in Shandong of the North China Plain during three haze events from 9 to 25 December 2021, named cases P1 (94.46 (30.85) μg m-3 for PM2.5 (nitrate)), P2 (148.95 (50.12) μg m-3) and P3 (88.03 (29.21) μg m-3), by using the Weather Research and Forecasting/Chemistry model with an integrated process rate analysis scheme and updated heterogeneous hydrolysis of dinitrogen pentoxide on the wet aerosol surface (HET-N2O5) and additional nitrous acid (HONO) sources (AS-HONO). The results showed that nitrate increases in the three cases were attributed to aerosol chemistry, whereas nitrate decreases were due mainly to the vertical mixing process in cases P1 and P2 and to the advection process in case P3. HET-N2O5 (the reaction of OH + NO2) contributed 45 % (51 %) of the HNO3 production rate during the study period. AS-HONO produced a nitrate enhancement of 24 % in case P1, 12 % in case P2 and 19 % in case P3, and a HNO3 production rate enhancement of 0.79- 0.97 (0.18- 0.60) μg m-3 h-1 through the reaction of OH + NO2 (HET-N2O5) in the three cases. This study implies that using suitable parameterization schemes for heterogeneous reactions on aerosol and ground surfaces and nitrate photolysis is vital in simulations of HONO and nitrate, and the MOSAIC module for aerosol water simulations needs to be improved.

Control of fine particulate nitrate during severe winter haze in "2+26" cities

The "2+26" cities, suffering the most severe winter haze pollution, have been the key region for air quality improvement in China. Increasing prominent nitrate pollution is one of the most challenging environmental issues in this region, necessitating development of an effective control strategy. Herein, we use observations, and state-of-the-art model simulations with scenario analysis and process analysis to quantify the effectiveness of the future SO2-NOX-VOC-NH3 emission control on nitrate pollution mitigation in "2+26" cities. Focusing on a serious winter haze episode, we find that limited NOX emission reduction alone in the short-term period is a less effective choice than VOC or NH3 emission reduction alone to decrease nitrate concentrations, due to the accelerated NOX-HNO3 conversion by atmospheric oxidants and the enhanced HNO3 to NO3- partition by ammonia, although deep NOX emission reduction is essential in the long-term period. The synergistic NH3 and VOC emission control is strongly recommended, which can counteract the adverse effects of nonlinear photochemistry and aerosol chemical feedback to decrease nitrate more. Such extra benefits will be reduced if the synergistic NH3 and VOC reduction is delayed, and thus reducing emission of multiple precursors is urgently required for the effective control of increasingly severe winter nitrate pollution in "2+26" cities.

The significant contribution of nitrate to a severe haze event in the winter of Guangzhou, China

A severe haze pollution occurred in Guangzhou from January 14 to 16, 2021, during which the mass concentration of PM2.5 ranged from 76 to 243 μg m-3. This level of pollution was rarely observed in recent years considering the improved air quality in Guangzhou. Therefore, it is crucial to comprehensively study the formation mechanisms of this severe haze pollution to prevent its reoccurrence. During the haze period, the concentrations of NO and NO2 sharply increased by 7.4 and 3.8 times, respectively, and total volatile organic compounds (TVOCs) increased 7 times, suggesting enhanced primary emissions from vehicles due to stagnant meteorological conditions. Nitrate concentration (43 ± 20 μg m-3) increased 6.7 times and became the dominant species in PM2.5 during the haze period. Notably, gaseous NH3, HONO and HNO3 also exhibited a sharp increase, suggesting the important role of nitrate chemistry in the evolution of haze pollution. The simulation results from chemical box model revealed that the OH + NO2 reaction was the dominant formation pathway for nitrate production (82 %) during the haze period. The net production rate of ROx radicals (including OH, HO2 and RO2) was 4.4 times higher during the haze period (5.8 ppb h-1) compared to the pre-haze period (1.3 ppb h-1). This was mainly attributed to the enhanced HONO and OVOCs photolysis, which increased from 0.6 ppb h-1 to 3.1 ppb h-1 and 0.4 ppb h-1 to 2.1 ppb h-1, respectively. Furthermore, the sensitivity tests demonstrated the reductions in VOCs and NOx were both beneficial for controlling nitrate production by influencing OH production and N2O5 uptake rate. These findings provide insights into the formation mechanisms of nitrate production during severe haze pollution and suggest that joint mitigation of PM2.5 and O3 can be achieved through the control of VOCs emission.

The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m-3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m-3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020-2021. Despite a 22~62% decline in NOx levels in 2020-2021, the increased O3 caused a similar NO3- concentration (20.69~23.00 μg m-3) in 2020-2021 to that (22.93 μg m-3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019-2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future.

Contrasting change trends in dry and wet nitrogen depositions during 2011 to 2020: Evidence from an agricultural catchment in subtropical Central China

Over the past decade, China has experienced a decline in atmospheric reactive nitrogen (Nr) emissions. Given that China's subtropical region is a significant nitrogen (N) deposition hotspot, it is essential to accurately quantify the ten-year variations in dry and wet N depositions in the context of reductions in atmospheric Nr emissions. Here, we evaluated the spatiotemporal variation in N deposition on forest, paddy field and tea field ecosystems in a typical subtropical agricultural catchment from 2011 to 2020. Our findings indicated a significant decrease in total N deposition in both the tea field ecosystem (41.5-30.5 kg N ha-1) and the forest ecosystem (40.8-25.7 kg N ha-1) (P < 0.05), but no significant change in the paddy field ecosystem (29.3-32.9 kg N ha-1). Specifically, dry N deposition exhibited significant declines except in the paddy field ecosystem, whereas wet N deposition had no significant change. The reduction in total oxidized and reduced N depositions in forest and tea field ecosystems is attributed to the decrease in NOx and NH3 emissions. Additionally, The ratio of NHx deposition to total N deposition all exceeded 0.5 in three ecosystems and the NHx/NOy ratio had an increasing trend (P < 0.05) in the paddy field, indicating that reactive N emissions from agricultural sources were the primary contributor to overall N deposition. Our study emphasizes that despite the decreasing trend in N deposition, it still exceeds the critical loads of natural ecosystems and requires stringent N emissions control, particularly from agricultural sources, in the future.

Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 μg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

Characteristics of secondary inorganic aerosols and contributions to PM2.5 pollution based on machine learning approach in Shandong Province

Primary emissions of particulate matter and gaseous pollutants, such as SO2 and NOx have decreased in China following the implementation of a series of policies by the Chinese government to address air pollution. However, controlling secondary inorganic aerosol pollution requires attention. This study examined the characteristics of the secondary conversion of nitrate (NO3-) and sulfate (SO42-) in three coastal cities of Shandong Province, namely Binzhou (BZ), Dongying (DY), and Weifang (WF), and an inland city, Jinan (JN), during December 2021. Furthermore, the Shapley Additive Explanation (SHAP), an interpretable attribution technique, was adopted to accurately calculate the contributions of secondary formations to PM2.5. The nitrogen oxidation rate exhibited a significant dependence on the concentration of O3. High humidity facilitates sulfur oxidation. Compared to BZ, DY, and WF, the secondary conversion of NO3- and SO42- was more intense in JN. The light-gradient boosting model outperformed the random forest and extreme-gradient boosting models, achieving a mean R2 value of 0.92. PM2.5 pollution events in BZ, DY, and WF were primarily attributable to biomass burning, whereas pollution in Jinan was contributed by the secondary formation of NO3- and vehicle emissions. Machine learning and the SHAP interpretable attribution technique offer a precise analysis of the causes of air pollution, showing high potential for addressing environmental concerns.

Reduced atmospheric sulfate enhances fine particulate nitrate formation in eastern China

Nitrate (NO3-) is a major component of atmospheric fine particles. Recent studies in eastern China have shown the increasing trend of NO3- in contrast to the ongoing control of nitrogen oxide (NOx). Here, we elucidate the effects of reduced sulfur dioxide (SO2) on the enhancement of NO3- formation based on field measurements at the summit of Mt. Tai (1534 m a.s.l.) and present detailed modelling analyses. From 2007 to 2018, the measured springtime concentrations of various primary pollutants and fine sulfate (SO42-) decreased sharply (-16.4 % to -89.7 %), whereas fine NO3- concentration increased by 22.8 %. The elevated NO3- levels cannot be explained by the changes in meteorological conditions or other related parameters but were primarily attributed to the considerable reduction in SO42- concentrations (-73.4 %). Results from a multi-phase chemical box model indicated that the reduced SO42- levels decreased the aerosol acidity and prompted the partitioning of HNO3 into the aerosol phase. WRF-Chem model analyses suggest that such a negative effect is a regional phenomenon throughout the planetary boundary layer over eastern China in spring. This study provides new insights into the worsening situation of NO3- aerosol pollution and has important implications for controlling haze pollution in China.

Significantly mitigating PM2.5 pollution level via reduction of NOx emission during wintertime

Despite considerable decreases in fine particulate matter (PM2.5) in Chinese megacities over the past decade, many second- and third-tier cities that distribute abundant industrial enterprises are still facing great challenges for PM2.5 further reduction under the recent policy background of eliminating heavily-polluted weather. In view of core effects of NOx on PM2.5, the deeper reductions of NOx in these cities are expected to break the plateau of PM2.5 decline, however, the link between NOx emission and PM2.5 mass loading is currently lacking. Herein, we progressively construct an evaluation system for PM2.5 productions based on daily NOx emissions in a typical industrial city (Jiyuan), considering a sequence of nested parameters involving evolutions of NO2 into nitric acid and then nitrate, and contributions of nitrate to PM2.5. The evaluation system was subsequently validated to better reproduce real increasing processes for PM2.5 pollution based on 19 pollution cases, with root mean square errors of 19.2 ± 16.4 %, suggesting the feasibility of developing NOx emission indicators linked to goals of mitigating atmospheric PM2.5. Additionally, further comparative results reveal that currently high NOx emissions in this industrial city severely hinder the achievement of atmospheric PM2.5 environmental capacity targets, especially in the scenarios of high initial PM2.5 level, low planetary boundary layer height and long pollution duration. It is anticipated that these methodologies and findings would supply guidelines for further regional PM2.5 mitigation, in which source-oriented NOx indicators could also provide some orientations for industrial cleaner production such as denitrification and low nitrogen combustion.

Concurrent measurements of nitrate at urban and suburban sites identify local nitrate formation as a driver for urban episodic PM2.5 pollution

Nitrate (NO3-) is often among the leading components of urban particulate matter (PM) during PM pollution episodes. However, the factors controlling its prevalence remain inadequately understood. In this work, we analyzed concurrent hourly monitoring data of NO3- in PM2.5 at a pair of urban and suburban locations (28 km apart) in Hong Kong for a period of two months. The concentration gradient in PM2.5 NO3- was 3.0 ± 2.9 (urban) vs. 1.3 ± 0.9 μg m-3 (suburban) while that for its precursors nitrogen oxides (NOx) was 38.1 vs 4.1 ppb. NO3- accounted for 45 % of the difference in PM2.5 between the sites. Both sites were characterized to have more available NH3 than HNO3. Urban nitrate episodes, defined as periods of urban-suburban NO3- difference exceeding 2 μg m-3, constituted 21 % of the total measurement hours, with an hourly NO3- average gradient of 4.2 and a peak value of 23.6 μg m-3. Our comparative analysis, together with 3-D air quality model simulations, indicates that the high NOx levels largely explain the excessive NO3- concentrations in our urban site, with the gas phase HNO3 formation reaction contributing significantly during the daytime and the N2O5 hydrolysis pathway playing a prominent role during nighttime. This study presents a first quantitative analysis that unambiguously shows local formation of NO3- in urban environments as a driver for urban episodic PM2.5 pollution, suggesting effective benefits of lowering urban NOx.

Double-Edged Role of VOCs Reduction in Nitrate Formation: Insights from Observations during the China International Import Expo 2018

Aerosol nitrate (NO3-) constitutes a significant component of fine particles in China. Prioritizing the control of volatile organic compounds (VOCs) is a crucial step toward achieving clean air, yet its impact on NO3- pollution remains inadequately understood. Here, we examined the role of VOCs in NO3- formation by combining comprehensive field measurements conducted during the China International Import Expo (CIIE) in Shanghai (from 10 October to 22 November 2018) and multiphase chemical modeling. Despite a decline in primary pollutants during the CIIE, NO3- levels increased compared to pre-CIIE and post-CIIE─NO3- concentrations decreased in the daytime (by -10 and -26%) while increasing in the nighttime (by 8 and 30%). Analysis of the observations and backward trajectory indicates that the diurnal variation in NO3- was mainly attributed to local chemistry rather than meteorological conditions. Decreasing VOCs lowered the daytime NO3- production by reducing the hydroxyl radical level, whereas the greater VOCs reduction at night than that in the daytime increased the nitrate radical level, thereby promoting the nocturnal NO3- production. These results reveal the double-edged role of VOCs in NO3- formation, underscoring the need for transferring large VOC-emitting enterprises from the daytime to the nighttime, which should be considered in formulating corresponding policies.

China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment

Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.

Heterogeneous uptake of NO2 by sodium acetate droplets and secondary nitrite aerosol formation

The high NO₃^- concentration in fine particulate matters (PM_2.5) during heavy haze events has attracted much attention, but the formation mechanism of nitrates remains largely uncertain, especially concerning heterogeneous uptake of NO_X by aqueous phase. In this work, the heterogeneous uptake of NO₂ by sodium acetate (NaAc) droplets with different NO₂ concentrations and relative humidity (RH) conditions is investigated by microscopic Fourier transform infrared spectrometer (micro-FTIR). The IR feature changes of aqueous droplets indicate the acetate depletion and nitrite formation in humid environment. This implies that acetate droplets can provide the alkaline aqueous circumstances caused by acetate hydrolysis and acetic acid (HAc) volatilization for nitrite formation during the NO₂ heterogeneous uptake. Meanwhile, the nitrite formation will exhibit a pH neutralizing effect on acetate hydrolysis, further facilitating HAc volatilization and acetate depletion. The heterogeneous uptake coefficient increases from 5.2 × 10^-6 to 1.27 × 10^-5 as RH decreases from 90% to 60% due to the enhanced HAc volatilization. Furthermore, no obvious change in uptake coefficient with different NO₂ concentrations is observed. This work may provide a new pathway for atmospheric nitrogen cycling and secondary nitrite aerosol formation.

What controls aerosol δ15N-NO3-? NOx emission sources vs. nitrogen isotope fractionation

Atmospheric δ¹⁵N-NO₃^- has been used to reveal NO_x (NO + NO₂) sources as NO₃^- is the ultimate sink of NO_x. However, it remains questionable whether the nitrogen isotope fractionation among NO_y (NO, NO₂, NO₃, N₂O₅, HNO₃ and NO₃^-) engender the misjudgment of NO_x emission sources by affecting δ¹⁵N-NO_y. To explore this issue, we integrated the dataset of aerosol δ¹⁵N-NO₃^- values and ratios of f_NO2 (f_NO2 = NO₂/(NO₂ + NO)), calculated the nitrogen isotope fractionation factors (Δ_s) among NO_y, compared the total energy consumption in Beijing-Tianjin-Hebei region (BTH) from 2013 to 2018. Results showed that, although the total energy consumption structure changed from 2013 to 2018 in BTH, there were fewer interannual variances of aerosol δ¹⁵N-NO₃^- values. Nitrogen isotope fractionation factors between NO and NO₂ (Δ₀), NO₂ and NO₃ (Δ₂), NO₂ and N₂O₅ (Δ₃), NO₂ and ClONO₂ (Δ₄) also displayed less interannual variations from 2013 to 2018 in BTH. But both aerosol δ¹⁵N-NO₃^- and Δ_s displayed significant seasonal patterns, and there was significant relationship between monthly aerosol δ¹⁵N-NO₃^- and Δ_s, which suggested that Δ_s have important influence on shaping aerosol δ¹⁵N-NO₃^- and further discriminating NO_x emission sources. This study implies that we should refine the Δ_s when employing atmospheric δ¹⁵N-NO₃^- to quantify NO_x source allocation.

Response of cross-correlations between high PM2.5 and O3 with increasing time scales to the COVID-19: different trends in BTH and PRD

The air pollution in China currently is characterized by high fine particulate matter (PM_2.5) and ozone (O₃) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM_2.5 and O₃ are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM_2.5 and O₃. Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM_2.5 and O₃ in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM_2.5 decreased while O₃ increased in most cities due to the effect of COVID-19, and the increase in O₃ is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM_2.5-O₃ DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM_2.5-O₃ VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM_2.5 and O₃ are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM_2.5-O₃ DHP coordinated control strategies.

Vertical measurements of stable nitrogen and oxygen isotope composition of fine particulate nitrate aerosol in Guangzhou city: Source apportionment and oxidation pathway

Nowadays, the emission source and formation mechanism of fine particulate nitrate (pNO₃^-) in China are mired in controversy. In this study, the stable nitrogen isotope (δ¹⁵N-NO₃^-) and triple oxygen isotope (Δ¹⁷O-NO₃^-) were determined for the pNO₃^- samples collected at three heights under different atmospheric oxidation capacity (AOC) (O_x = O₃ + NO₂: 107 ± 29 μg m^-3 at ground, 102 ± 28 μg m^-3 at 118 m, 122 ± 23 μg m^-3 at 488 m) conditions during the sampling period based on the Canton Tower, Guangzhou, China. The Bayesian mixing model showed that coal combustion was the largest contributor to pNO₃^- in this city, followed by biomass burning, vehicle exhaust, and soil emission. Interestingly, we found that vertical NO_x and pNO₃^- concentrations displayed an opposite pattern owing to the different formation mechanisms among heights. The average contributions of oxidation pathways for (NO₂ + OH, P1), (NO₃ + DMS/HC, P2), and (N₂O₅ + H₂O, P3) were 61 %, 12 %, and 27 % at the ground, respectively, and these values would vary greatly among heights. These results implied that both AOC and NO_x loading played an important role in pNO₃^- production. The pNO₃^- displayed a positive correlation with NO_x (r = 0.95) with an enhanced contribution of the P1 pathway under the relatively high AOC condition. However, pNO₃^- has a negative correlation with NO_x (r = -0.99) with a rise of heterogeneous reaction (P2 and P3) under the relatively low AOC condition. Therefore, the current emission control strategy for air pollution in China needs to consider the AOC conditions among regions to effectively mitigate particulate air pollution.

Contributions of various driving factors to air pollution events: Interpretability analysis from Machine learning perspective

The air quality in China has been improved substantially, however fine particulate matter (PM_2.5) still remain at a high level in many areas. PM_2.5 pollution is a complex process that is attributed to gaseous precursors, chemical, and meteorological factors. Quantifying the contribution of each variable to air pollution can facilitate the formulation of effective policies to precisely eliminate air pollution. In this study, we first used decision plot to map out the decision process of the Random Forest (RF) model for a single hourly data set and constructed a framework for analyzing the causes of air pollution using multiple interpretable methods. Permutation importance was used to qualitatively analyze the effect of each variable on PM_2.5 concentrations. The sensitivity of secondary inorganic aerosols (SIA): SO₄^2-, NO₃^- and NH₄⁺ to PM_2.5 was verified by Partial dependence plot (PDP). Shapley Additive Explanation (Shapley) was used to quantify the contribution of drivers behind the ten air pollution events. The RF model can accurately predict PM_2.5 concentrations, with determination coefficient (R²) of 0.94, root mean square error (RMSE) and mean absolute error (MAE) of 9.4 μg/m³ and 5.7 μg/m³, respectively. This study revealed that the order of sensitivity of SIA to PM_2.5 was NH₄⁺＞NO₃^-＞SO₄^2-. Fossil fuel and biomass combustion may be contributing factors to air pollution events in Zibo in 2021 autumn-winter. NH₄⁺ contributed 19.9-65.4 μg/m³ among ten air pollution events (APs). K, NO₃^-, EC and OC were the other main drivers, contributing 8.7 ± 2.7 μg/m³, 6.8 ± 7.5 μg/m³, 3.6 ± 5.8 μg/m³ and 2.5 ± 2.0 μg/m³, respectively. Lower temperature and higher humidity were vital factors that promoted the formation of NO₃^-. Our study may provide a methodological framework for precise air pollution management.

Change in Air Quality during 2014-2021 in Jinan City in China and Its Influencing Factors

Air pollution affects climate change, food production, traffic safety, and human health. In this paper, we analyze the changes in air quality index (AQI) and concentrations of six air pollutants in Jinan during 2014-2021. The results indicate that the annual average concentrations of PM₁₀, PM_2.5, NO₂, SO₂, CO, and O₃ and AQI values all declined year after year during 2014-2021. Compared with 2014, AQI in Jinan City fell by 27.3% in 2021. Air quality in the four seasons of 2021 was obviously better than that in 2014. PM_2.5 concentration was the highest in winter and PM_2.5 concentration was the lowest in summer, while it was the opposite for O₃ concentration. AQI in Jinan during the COVID epoch in 2020 was remarkably lower compared with that during the same epoch in 2021. Nevertheless, air quality during the post-COVID epoch in 2020 conspicuously deteriorated compared with that in 2021. Socioeconomic elements were the main reasons for the changes in air quality. AQI in Jinan was majorly influenced by energy consumption per 10,000-yuan GDP (ECPGDP), SO₂ emissions (SDE), NOx emissions (NOE), particulate emissions (PE), PM_2.5, and PM₁₀. Clean policies in Jinan City played a key role in improving air quality. Unfavorable meteorological conditions led to heavy pollution weather in the winter. These results could provide a scientific reference for the control of air pollution in Jinan City.

Transport Pathways of Nitrate Formed from Nocturnal N2O5 Hydrolysis Aloft to the Ground Level in Winter North China Plain

Particulate nitrate (NO₃^-) has currently become the major component of fine particles in the North China Plain (NCP) during winter haze episodes. However, the contributions of formation pathways to ground NO₃^- in the NCP are not fully understood. Herein, the NO₃^- formation pathways were comprehensively investigated based on model simulations combined with two-month field measurements at a rural site in the winter NCP. The results indicated that the nocturnal chemistry of N₂O₅ hydrolysis aloft could contribute evidently to ground NO₃^- at the rural site during the pollution episodes with high aerosol water contents, achieving the contribution percentages of 25.2-30.4% of the total. In addition to the commonly proposed vertical mixing of breaking nocturnal boundary layer in the early morning, two additional transport pathways (frontal downdrafts and downslope mountain breezes) in the nighttime were found to make higher contributions to ground NO₃^-. Considering the dominant role (69.6-74.8%) of diurnal chemistry in NO₃^- formation, reduction of NO_x emissions in the daytime may be an effective control measure for reducing regional NO₃^- in the NCP.

Exploring the driving factors of haze events in Beijing during Chinese New Year holidays in 2020 and 2021 under the influence of COVID-19 pandemic

Unexpected outbreak of the 2019 novel coronavirus (COVID-19) has profoundly altered the way of human life and production activity, which posed visible impacts on PM_2.5 and its chemical species. The abruptly emergency reduction in human activities provided an opportunity to explore the synergetic impacts of multi-factors on shaping PM_2.5 pollution. Here, we conducted two comprehensive observation measurements of PM_2.5 and its chemical species from 1 January to 16 February in Beijing 2020 and the same lunar date in 2021, to investigate temporal variations and reveal the driving factors of haze before and after Chinese New Year (CNY). Results show that mean PM_2.5 concentrations during the whole observation were 63.83 and 66.86 μg/m³ in 2020 and 2021, respectively. Higher secondary inorganic species were observed after CNY, and K⁺, Cl^- showed three prominent peaks which associated closely with fireworks burnings from suburb Beijing and surroundings, verifying that they could be used as two representative tracers of fireworks. Further, we explored the impacts of meteorological conditions, regional transportation as well as chemical reactions on PM_2.5. We found that unfavorable meteorological conditions accounted for 11.0 % and 16.9 % of PM_2.5 during CNY holidays in 2020 and 2021, respectively. Regional transport from southwest and southeast (south) played an important role on PM_2.5 during the two observation periods. Higher ratio of NO₃^-/SO₄^2- were observed under high O_X and low RH conditions, suggesting the major pathway of NO₃^- and SO₄^2- formation could be photochemical process and aqueous-phase reaction. Additionally, nocturnal chemistry facilitated the formation of secondary components of both inorganic and organic. This study promotes understandings of PM_2.5 pollution in winter under the influence of COVID-19 pandemic and provides a well reference for haze and PM_2.5 control in future.

Comparative analysis of nitrate evolution patterns during pollution episodes: Method development and results from Tianjin, China

Particulate nitrate plays an increasingly important role in the formation of air pollution process, while the main mechanisms of nitrate concentration change are different in each stage, same as the driving factors. In this study, we proposed an episode-based analysis to illustrate the typical nitrate evolution patterns and identify the possible impacting factors in different evolution stages. Applying into twelve air pollution episodes, three typical patterns of nitrate evolution were abstracted, and the corresponding conceptual models were constructed. All the pollution episodes were grouped by their evolving shapes, which were driven by physical and chemical processes. Episodes started slowly typically arose from gradual pollutant accumulation, both locally and regionally, and chemical formation under high humidity. Type 1 ("hump-shaped type"), accounting for 66.3 % of the total episode durations, including two "peak" concentrations, displays a rapid growth rate which could up to 4.6 μg m^-3 h^-1 in average, mainly relying on the sharp drop in the planetary boundary layer height. Short scavenging processes and thoroughly dissipated stages of the pollution episodes always accompanied by strong north wind affected by Siberia-Mongolia cold current. Type 2 ("triangle-shaped type", 24.3 %) shows a gentle growth rate and short duration. Compared with Type 1, chemical process may be more important "source" for the increase of nitrate concentration during Type 2. Type 3 ("trapezoid-shaped type", 9.4 %) presents a long platform stage, during which high humidity (RH > 90 %) provides favorable conditions for wet removal and secondary production, and the updraft can carry pollutants to high altitude. The source and sink are roughly balanced for Type 3. Our study highlights the importance of pattern identification for understanding the nitrate evolution behavior, it may also provide insights for pollution prediction and scientific mitigation strategies.

Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 3. Mechanism assessment of O3 trends by a model

A multiscale analysis of meteorological trends was carried out to investigate the impacts of the large-scale circulation types as well as the local-scale key weather elements on the complex air pollutants, i.e., PM_2.5 and O₃ in China. Following accompanying papers on synoptic circulation impact and key weather elements and emission contributions (Gong et al., 2022a; Gong et al., 2022b), an emission-driven Observation-based Box Model (e-OBM) was developed to study the impact mechanisms on O₃ trend and quantitatively assess the effects of variation in the emissions control over 2013-2020 for Beijing, Chengdu, Guangzhou and Shanghai. Compared with the original OBM, the e-OBM not only improves the performance to simulate the hourly O₃ peak concentration in daytime, but also reasonably reproduces the maximum daily 8-hour average (MDA8) O₃ concentrations in the four cities. Based upon the sensitivity experiments, it is found that the meteorology is the dominant driver for the MDA8 O₃ trend, contributing from about 32 % to 139 % to the variations. From the mechanistic point of view, the variations of meteorology lead to the enhancement of atmospheric oxidation capacity and the acceleration of O₃ production. Further evaluation to the emission changes in four cities shows that the O₃-precursors relationships of the four cities have been changed from the VOC-limited regime in 2013 to the transition regime or near-transition regime in 2020. Though the NO_x/VOCs ratios have been obviously decreased, the emission reductions up to 2020 were still not enough to mitigate O₃ pollution in these cities. It is emphasized in this study that the strengthened control measures with maintaining a certain ratio of NO_x and VOCs should be implemented to further curb the increasing trend of O₃ in urban areas.

Responses of sulfate and nitrate to anthropogenic emission changes in eastern China - in perspective of long-term variations

We investigate responses of sulfate (SO₄^2-) and nitrate (NO₃^-) to anthropogenic emission changes in 2006-2017 by fixing meteorology at the 2009 level using nested 3D chemical transport model GEOS-Chem. We find that sulfate concentration decreases following SO₂ emissions, but with a relatively smaller reduction rate (by 16 % in North China Plain (NCP) and 28 % in Yangtze River Delta (YRD)) due to larger sulfur oxidation ratio (SOR) at lower SO₂ level. SOR follows a power law with SO₂ emissions in general except in winter in NCP, when and where both SO₂ emission reduction and atmospheric oxidation capacity are critical to the inter-annual variations of SOR. Nitrate concentration ([pNO₃^-]) decreases along with NOx emission reduction in summer, but increases slightly in winter in 2011-2017. Equilibrium with gas phase HNO₃, NO₃^- in particle phase (pNO₃^-) is determined by total HNO₃ (TN = [pNO₃^-] + [gHNO₃]) oxidized from NO₂ and gas-particle partitioning (ε(NO₃^-) = [pNO₃^-]/TN). TN is decreasing faster in summer (~33 %) than in winter (~25 %) in 2011-2017. In contrast, ε(NO₃^-) changes marginally in summer (within 5 %) but increases by 36 % in NCP and by 51 % in YRD in winter in 2006-2017. The increasing of ε(NO₃^-) in winter is attributed to the strong reduction of [pSO₄^2-], which increases the relative abundance of NH₃ and thus favors partitioning of NO₃^- to the particle phase. The effect of increasing ε(NO₃^-) overcomes that of decreasing TN in winter. We suggest reduce SO₂ emissions to further reduce [pSO₄^2-] in eastern China. In addition, we recommend reduce NOx emissions in summer, and reduce atmospheric oxidation capacity and relative abundance of NH₃ in winter to reduce [pNO₃^-].

Investigation into the differences and relationships between gasSOA and aqSOA in winter haze pollution on Chongming Island, Shanghai, based on VOCs observation

To investigate the formation of secondary organic aerosol (SOA) under current atmospheric conditions, we conducted a field observation of SOA precursors in the downwind region of the Yangtze River Delta (YRD) in winter 2019 using a variety of offline and online instruments. During the entire observation period, the averaged fine particulate SOA was 7.9 ± 2.3 μg m^-3, with precursor concentrations of 31 ± 11 ppbv for the measured volatile organic compounds (VOCs) and 16 ± 12 ppbv for NOx. Compared to those on the clean days, SOA on the haze days increased by a factor of 1.6, while the VOC and NOx increased by a factor of 1.3 and 2.0, respectively. Aerosol liquid water content (ALWC) and oxygenated VOCs (OVOCs, including acetaldehyde, formic acid, acetone, acetic acid, methyl ethyl ketone, and methylglyoxal) relationships suggested that the gasSOA and aqSOA occurred simultaneously on Chongming Island in winter. The gasSOA was primarily formed by the oxidation of aromatics and NOx at low RH (RH < 80%) conditions. In contrast, the aqSOA was formed under higher RH (RH > 80%) conditions via a combination of daytime photochemical aqueous phase processes of water-soluble OVOCs and nocturnal dark aqueous phase processes of primary emissions from biomass. The inversed higher mass ratio of NACs to (benzene + toluene) and nitrogen oxidation ratio (NOR) in the daytime during the gasSOA-dominated haze periods indicated that gasSOA could be transformed to aqSOA at high NOx levels. Our results also suggested the importance of NOx and VOC reduction measures in directly mitigating gasSOA and indirectly mitigating aqSOA during winter haze pollution.

Formation mechanism and control strategy for particulate nitrate in China

Over the past decade, fine particulate matter (PM) pollution in China has been abated significantly, benefiting from strict emission control measures, but particulate nitrate continues to rise. Here, we review the progress in particulate nitrate (pNO₃^-) pollution characterization, nitrate formation mechanisms, and the proposed control strategies in China. The spatial and temporal distributions of pNO₃^- are summarized. The current status of knowledge on the chemical mechanism is updated, and the significance of its formation pathways is assessed by various approaches such as field observation and modelling of nitrate production rate, as well as isotopic analysis. The factors impacting pNO₃^- formation and the corresponding pollution regulation strategies are discussed, in which the importance of atmospheric oxidation capacity and ammonia are addressed. Finally, the challenges and open questions in pNO₃^- pollution control in China are outlined.

Effects of anthropogenic precursor emissions and meteorological conditions on PM2.5 concentrations over the "2+26" cities of northern China

Elucidating the characteristics and influencing mechanisms of PM_2.5 concentrations is the premise and key to the precise prevention and control of air pollution. However, the temporal and spatial heterogeneity of PM_2.5 concentrations and its driving mechanism are complex and need to be further analyzed. We analyzed the temporal and spatial variations of PM_2.5 concentrations in the "2 + 26" cities from 2015 to 2021, and quantified the influence of meteorological factors and anthropogenic emissions and their interactions on PM_2.5 concentrations based on geographic detector model. We find the inter-annual and inter-season PM_2.5 concentrations show downward trend from 2015 to 2021, and the inter-month PM_2.5 concentrations present a U-shaped distribution. The PM_2.5 concentrations in the "2 + 26" cities manifest a spatial distribution pattern of high in the south and low in the north, and high in the middle and low in the surroundings. Meteorological conditions have stronger effects on PM_2.5 concentrations than anthropogenic emissions, and planetary boundary layer height and temperature are the two main driving factors at the annual scale. On the seasonal scale, sunshine duration is the dominant factor of PM_2.5 concentrations in summer and autumn, and planetary boundary layer height is the dominant factor of PM_2.5 concentrations in winter. The effect of anthropogenic emissions on PM_2.5 concentration is higher in winter and spring than in summer and autumn, and ammonia and ozone have stronger effects on PM_2.5 concentrations than other anthropogenic emissions. Interactions between the factors significantly enhance the PM_2.5 concentrations. The interactions between planetary boundary layer height and other impacting factors play dominant roles on PM_2.5 concentrations at annual scale and in winter. Our results not only provide crucial information for further developing air quality policies of the "2 + 26" cities, but also bear out several important implications for clean air policies in China and other regions of the world.

Dramatic changes in aerosol composition during the 2016-2020 heating seasons in Beijing-Tianjin-Hebei region and its surrounding areas: The role of primary pollutants and secondary aerosol formation

With the implementation of a series of air pollution mitigation strategies during the past decade, great air quality improvements have been observed in the BTH region. Despite of significant decreases in gaseous pollutants, such as SO₂ and NO₂, the enhancement of secondary aerosol formation was observed. NO₃^- has surpassed SO₄^2- and OM to become the dominant PM_2.5 component. We find that the reduction of POC mainly dominated the decreasing trend of OC. As for secondary inorganic components, the key processes or factors controlling the spatial-temporal variation characteristics were different. The areas with large SO₄^2- concentrations corresponded well to those with high SO₂ concentrations, while the synchronized NO₃^- better followed spatial patterns in O₃ than NO₂. From 2016 to 2020, the response of SO₄^2- to SO₂ was close to a linear function, while the reaction of NO₃^- to the decrease of NO₂ displayed nonlinear behavior. Such different relationships indicated that SO₄^2- was predominantly controlled by SO₂, while NO₃^- was not only related to NO₂ but also determined by the secondary conversion process. The ratios of SO₄^2-, NO₃^-, NH₄⁺, and OC to EC between 2016 and 2020 were generally higher than 1 in typical BTH cities, and the ratio of NO₃^- to EC was exceptionally high, with a range reaching up to 200 %. Besides, this ratio coincided well with the enhancement of O_x, indicating the potential role of O_x to secondary NO₃^- formation. The diurnal cycle of NO₃^-, O₃, and NO₂ concentration change rate indicated that the relative increase of O₃ during nighttime may offset the effectiveness of NO_X emission reduction. This study provided observational evidence of enhanced secondary NO₃^- formation with the rising trend of atmospheric oxidation and emphasized the importance of nighttime chemistry for NO₃^- formation in the BTH region.

Secondary inorganic aerosol chemistry and its impact on atmospheric visibility over an ammonia-rich urban area in Central Taiwan

This study investigated the hourly inorganic aerosol chemistry and its impact on atmospheric visibility over an urban area in Central Taiwan, by relying on measurements of aerosol light extinction, inorganic gases, and PM_2.5 water-soluble ions (WSIs), and simulations from a thermodynamic equilibrium model. On average, the sulfate (SO₄^2-), nitrate (NO₃^-), and ammonium (NH₄⁺) components (SNA) contributed ∼90% of WSI concentrations, which in turn made up about 50% of the PM_2.5 mass. During the entire observation period, PM_2.5 and SNA concentrations, aerosol pH, aerosol liquid water content (ALWC), and sulfur and nitrogen conversion ratios all increased with decreasing visibility. In particular, the NO₃^- contribution to PM_2.5 increased, whereas the SO₄^2- contribution decreased, with decreasing visibility. The diurnal variations of the above parameters indicate that the interaction and likely mutual promotion between NO₃^- and ALWC enhanced the hygroscopicity and aqueous-phase reactions conducive for NO₃^- formation, thus led to severely impaired visibility. The high relative humidity (RH) at the study area (average 70.7%) was a necessary but not sole factor leading to enhanced NO₃^- formation, which was more directly associated with elevated ALWC and aerosol pH. Simulations from the thermodynamic model depict that the inorganic aerosol system in the study area was characterized by fully neutralized SO₄^2- (i.e. a saturated factor in visibility reduction) and excess NH₄⁺ amidst a NH₃-rich environment. As a result, PM_2.5 composition was most sensitive to gas-phase HNO₃, and hence NOx, and relatively insensitive to NH₃. Consequently, a reduction of NOx would result in instantaneous cuts of NO₃^-, PM_2.5, and ALWC, and hence improved visibility. On the other hand, a substantial amount of NH₃ reduction (>70%) would be required to lower the aerosol pH, driving more than 50% of the particulate phase NO₃^- to the gas phase, thereby making NH₃ a limiting factor in shifting PM_2.5 composition.

Haze caused by NOx oxidation under restricted residential and industrial activities in a mega city in the south of North China Plain

The formation of secondary aerosol species, including nitrate and sulfate, induces severe haze in the North China Plain. However, despite substantial reductions in anthropogenic pollutants due to severe restriction of residential and industrial activities in 2020 to stop the spread of COVID-19, haze still formed in Zhengzhou. We compared ionic compositions of PM_2.5 during the period of the restriction with that immediately before the restriction and in the comparison period in 2019 to investigate the processes that caused the haze. The average concentration of PM_2.5 was 83.9 μg m^-3 in the restriction period, 241.8 μg m^-3 before the restriction, and 94.0 μg m^-3 in 2019. Nitrate was the largest contributor to the PM_2.5 in all periods, with an average mass fraction of 24%-30%. The average molar concentration of total nitrogen compounds (NO_x + nitrate) was 0.89 μmol m^-3 in the restriction period, which was much lower than that in the non-restriction periods (1.85-2.74 μmol m^-3). In contrast, the concentration of sulfur compounds (SO₂ + sulfate) was 0.34-0.39 μmol m^-3 in all periods. The conversion rate of NO_x to nitrate (NOR) was 0.35 in the restriction period, significantly higher than that before the restriction (0.26) and in 2019 (0.25). NOR was higher with relative humidity in 40-80% in the restriction period than in the other two periods, whereas the conversion rate of SO₂ to sulfate did not, indicating nitrate formation was more efficient during the restriction. When O₃ occupied more than half of the oxidants (O_x = O₃ + NO₂), NOR increased rapidly with the ratio of O₃ to O_x and was much higher in the daytime than nighttime. Therefore, haze in the restriction period was caused by increased NO_x-to-nitrate conversion driven by photochemical reactions.

Variation of pollution sources and health effects on air pollution before and during COVID-19 pandemic in Linfen, Fenwei Plain

Stringent pollution control measures are generally applied to improve air quality, especially in the Spring Festival in China. Meanwhile, human activities are reduced significantly due to nationwide lockdown measures to curtail the COVID-19 spreading in 2020. Herein, to better understand the influence of control measures and meteorology on air pollution, this study compared the variation of pollution source and their health risk during the 2019 and 2020 Spring Festival in Linfen, China. Results revealed that the average concentration of PM_2.5 in 2020 decreased by 39.0% when compared to the 2019 Spring Festival. Organic carbon (OC) and SO₄^2- were the primary contributor to PM_2.5 with the value of 19.5% (21.1%) and 23.5% (25.5%) in 2019 (2020) Spring Festival, respectively. Based on the positive matrix factorization (PMF) model, six pollution sources of PM_2.5 were indicated. Vehicle emissions (VE) had the maximum reduction in pollution source concentration (28.39 μg· m^-3), followed by dust fall (DF) (11.47 μg· m^-3), firework burning (FB) (10.39 μg· m^-3), coal combustion (CC) (8.54 μg· m^-3), and secondary inorganic aerosol (SIA) (3.95 μg· m^-3). However, the apportionment concentration of biomass burning (BB) increased by 78.7%, indicating a significant increase in biomass combustion under control measures. PAHs-lifetime lung cancer risk (ILCR) of VE, CC, FB, BB, and DF, decreased by 44.6%, 43.2%, 34.1%, 21.3%, and 2.0%, respectively. Additionally, the average contribution of meteorological conditions on PM_2.5 in 2020 increased by 20.21% compared to 2019 Spring Festival, demonstrating that meteorological conditions played a crucial role in located air pollution. This study revealed that the existing control measures in Linfen were efficient to reduce air pollution and health risk, whereas more BB emissions were worthy of further attention. Furthermore, the result was conducive to developing more effective control measures and putting more attention into unfavorable meteorological conditions in Linfen.

Formation pathway of secondary inorganic aerosol and its influencing factors in Northern China: Comparison between urban and rural sites

Secondary inorganic aerosol, including sulfate, nitrate, and ammonium (SNA), is a significant source of PM_2.5 during haze episodes in Northern China. A series of high-time-resolution instruments were used in collecting PM_2.5 chemical components and gaseous pollutants during a regional heavy pollution process from January 12-25, 2018, at urban and rural sites. SNA, accounting for >50% of PM_2.5 at both sites, had greater importance on haze formation. Gas-phase and N₂O₅ hydrolysis reactions were the main formation pathways of nitrate during the daytime and nighttime, respectively. The OH radical was the primary factor for gas-phase reactions. HONO photolysis played a more critical role in OH radical formation when O₃ concentration decreased during the haze episode. N₂O₅ hydrolysis reaction was mainly affected by O₃ and aerosol water content. High relative humidity, aerosol water content, and N₂O₅ concentrations at the urban site enhanced the hydrolysis reactions more than those at the rural site. The aqueous-phase reactions dominated the sulfate formation with the highest rate of transition metal ion catalytic and H₂O₂ oxidation reactions at the urban and rural sites, respectively. Elevated relative humidity and particle acidity at the urban site resulted in a higher formation rate of aqueous-phase sulfate than at the rural site. The gas-particle partition coefficient of NH₃ had a negative correlation with the particle pH, and the presence of NH₃ could promote the increase of SNA concentration. Thus, more attention should be paid to the differences in SNA formation between urban and rural regions when formulating air quality policies.

Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2.5 pollution

PM_2.5 pollution is a complex process mainly affected by emission sources and meteorological conditions. However, it is hard to accurately assess the effects of emission sources and meteorological conditions on the variation of PM_2.5 concentrations in the complex atmospheric environment. In this study, the Random Forest model with Shapley Additive exPlanations (RF-SHAP) and Partial Dependence Plot (RF-PDP) was combined with Positive Matrix Factorization (PMF) to evaluate the impacts of various factors on PM_2.5 pollution. The results show that anthropogenic emissions and meteorological conditions contributed about 67% (40.5 μg/m³) and 33% (19.7 μg/m³) to variation in PM_2.5 concentrations, respectively. Specifically, secondary nitrate (SN) had the greatest impact among all sources (about 45%). Hence, we further explore the impacts of the primary sources and meteorological conditions on SN formation. Coal combustion and vehicle emissions significantly contribute to the formation of SN by providing a large number of precursor NO_X. Additionally, the RF-PDP method was further employed to estimate the synergistic effects of primary sources and meteorological conditions on SN formation. The results help reveal strategies to simultaneously reduce SN by controlling primary emissions under suitable meteorological conditions. This work also suggests that the machine learning model can utilize online datasets well and provide a reliable approach for analyzing the causes of PM_2.5 pollution.

Decade-long trends in chemical component properties of PM2.5 in Beijing, China (2011-2020)

A 10-year-long measurement of water-soluble inorganic ions in PM_2.5 was made in Beijing from June 2011 to December 2020, to investigate the interannual trends of chemical characteristics of PM_2.5 and to provide insights into the future prevention and control of PM_2.5 pollution. From 2011 to 2020, with the implementation of strict air pollution control strategies, significant changes of PM_2.5 have been observed in Beijing, with NO₃^-, SO₄^2- and NH₄⁺ decreasing at rates of 5.10, 8.80 and 7.64% yr^-1 respectively. The percentages of NO₃^- and SO₄^2- under elevated pollution levels were investigated. When PM_2.5 values fell in the range of 0-400 μg m^-3, NO₃^-/ SO₄^2- values were mostly higher than 1 and showed upward trends from 2011 to 2020. However, under extremely heavy haze conditions, SO₄^2- dominated PM_2.5 formation. This result was closely related to the change characteristics of the oxidation ratio of sulfate (SOR), the oxidation ratio of nitrate (NOR) and gaseous precursors under different pollution levels. The change characteristics of NOR and SOR under elevated PM_2.5 levels indicated that the aqueous phase oxidation was the key process driving SO₄^2- formation; while as for NO₃^-, in addition to the availability of NH₄⁺, the atmospheric oxidation capacity made crucial roles. The analysis of typical haze episodes during the past decade indicated that the emission reduction of gaseous pollutants, especially SO₂, made great contributions to the improved PM_2.5 air quality in Beijing. We highlighted that future efforts should focus on enhanced reduction of NO₂ emission and control of atmospheric oxidation capacity to further reduce particulate nitrate formation.

Modeling particulate nitrate in China: Current findings and future directions

Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.