Detailed Analysis of Estimated pH, Activity Coefficients, and Ion Concentrations between the Three Aerosol Thermodynamic Models

Quantifying HONO Production from Nitrate Photolysis in a Polluted Atmosphere

The photolysis of particulate nitrate (pNO3-) has been suggested to be an important source of nitrous acid (HONO) in the troposphere. However, determining the photolysis rate constant of pNO3- (jpNO3-) suffers from high uncertainty. Prior laboratory measurements of jpNO3- using aerosol filters have been complicated by the "shadow effect"─a phenomenon of light extinction within aerosol layers that potentially skews these measurements. We developed a method to correct the shadow effect on the photolysis rate constant of pNO3- for HONO production (jpNO3- → HONO) using aerosol filters with identical chemical compositions but different aerosol loadings. We applied the method to quantify jpNO3- → HONO over the North China Plain (NCP) during the winter haze period. After correcting for the shadow effect, the normalized average jpNO3- → HONO at 5 °C increased from 5.89 × 10-6 s-1 to 1.72 × 10-5 s-1. The jpNO3- → HONO decreased with increasing pH and nitrate proportions in PM2.5 and had no correlation with nitrate concentrations. A parametrization for jpNO3- → HONO was developed for model simulation of HONO production in NCP and similar environments.

Regime shift in secondary inorganic aerosol formation and nitrogen deposition in the rural United States

Secondary inorganic aerosols play an important role in air pollution and climate change, and their formation modulates the atmospheric deposition of reactive nitrogen (including oxidized and reduced nitrogen), thus impacting the nitrogen cycle. Large-scale and long-term analyses of secondary inorganic aerosol formation based on model simulations have substantial uncertainties. Here we improve constraints on secondary inorganic aerosol formation using decade-long in situ observations of aerosol composition and gaseous precursors from multiple monitoring networks across the United States. We reveal a shift in the secondary inorganic aerosol formation regime in the rural United States between 2011 and 2020, making rural areas less sensitive to changes in ammonia concentrations and shortening the effective atmospheric lifetime of reduced forms of reactive nitrogen. This leads to potential increases in reactive nitrogen deposition near ammonia emission hotspots, with ecosystem impacts warranting further investigation. Ammonia (NH3), a critical but not directly regulated precursor of fine particulate matter in the United States, has been increasingly scrutinized to improve air quality. Our findings, however, show that controlling NH3 became significantly less effective for mitigating fine particulate matter in the rural United States. We highlight the need for more collocated aerosol and precursor observations for better characterization of secondary inorganic aerosols formation in urban areas.

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.

Dissociation constants of relevant secondary organic aerosol components in the atmosphere

The presented studies focus on measuring the determination of the acidity constant (pKa) of relevant secondary organic aerosol components. For our research, we selected important oxidation products (mainly carboxylic acids) of the most abundant terpene compounds, such as α-pinene, β-pinene, β-caryophyllene, and δ-3-carene. The research covered the synthesis and determination of the acidity constant of selected compounds. We used three methods to measure the acidity constant, i.e., 1H NMR titration, pH-metric titration, Bates-Schwarzenbach spectrophotometric method. Moreover, the pKa values were calculated with Marvin 21.17.0 software to compare the experimentally derived values with those calculated from the chemical structure. pKa values measured with 1H NMR titration ranged from 3.51 ± 0.01 for terebic acid to 5.18 ± 0.06 for β-norcaryophyllonic acid. Moreover, the data determined by the 1H NMR method revealed a good correlation with the data obtained with the commonly used potentiometric and UV-spectroscopic methods (R2 = 0.92). In contrast, the comparison with in silico results exhibits a relatively low correlation (R2Marvin = 0.66). We found that most of the values calculated with the Marvin Program are lower than experimental values obtained with pH-metric titration with an average difference of 0.44 pKa units. For di- and tricarboxylic acids, we obtained two and three pKa values, respectively. A good correlation with the literature values was observed, for example, Howell and Fisher (1958) used pH-metric titration and measured pKa1 and pKa2 to be 4.48 and 5.48, while our results are 4.24 ± 0.10 and 5.40 ± 0.02, respectively.

Primary sources of HONO vary during the daytime: Insights based on a field campaign

Nitrous acid (HONO) is an established precursor of hydroxyl (OH) radical and has significant impacts on the formation of PM2.5 and O3. Despite extensive research on HONO observation in recent years, knowledge regarding its sources and sinks in urban areas remains inadequate. In this study, we monitored the atmospheric concentrations of HONO and related pollutants, including gaseous nitric acid and particulate nitrate, simultaneously at a supersite in downtown Chengdu, a megacity in southwestern China during spring, when was chosen due to its tolerance for both PM2.5 and O3 pollution. Furthermore, we employed the random forest model to fill the missing data of HONO, which exhibited good predictive performance (R2 = 0.96, RMSE = 0.36 ppbv). During this campaign, the average mixing ratio of HONO was measured to be 1.0 ± 0.7 ppbv. Notably, during periods of high O3 and PM2.5 concentrations, the mixing ratio of HONO was >50 % higher compared to the clean period. We developed a comprehensive parameterization scheme for the HONO budget, and it performed well in simulating diurnal variations of HONO. Based on the HONO budget analysis, we identified different mechanisms that dominate HONO formation at different times of the day. Vehicle emissions and NO2 heterogeneous conversions were found to be the primary sources of HONO during nighttime (21.0 %, 30.2 %, respectively, from 18:00 to 7:00 the next day). In the morning (7:00-12:00), NO2 heterogeneous conversions and the reaction of NO with OH became the main sources (35.0 %, 32.2 %, respectively). However, in the afternoon (12:00-18:00), the heterogeneous photolysis of HNO3 on PM2.5 was identified as the most substantial source of HONO (contributing 52.5 %). This study highlights the significant variations in primary HONO sources throughout the day.

Role of Carbon Dioxide, Ammonia, and Organic Acids in Buffering Atmospheric Acidity: The Distinct Contribution in Clouds and Aerosols

Acidity is one central parameter in atmospheric multiphase reactions, influencing aerosol formation and its effects on climate, health, and ecosystems. Weak acids and bases, mainly CO2, NH3, and organic acids, are long considered to play a role in regulating atmospheric acidity. However, unlike strong acids and bases, their importance and influencing mechanisms in a given aerosol or cloud droplet system remain to be clarified. Here, we investigate this issue with new insights provided by recent advances in the field, in particular, the multiphase buffer theory. We show that, in general, aerosol acidity is primarily buffered by NH3, with a negligible contribution from CO2 and a potential contribution from organic acids under certain conditions. For fogs, clouds, and rains, CO2, organic acids, and NH3 may all provide certain buffering under higher pH levels (pH > ∼4). Despite the 104to 107 lower abundance of NH3 and organic weak acids, their buffering effect can still be comparable to that of CO2. This is because the cloud pH is at the very far end of the CO2 multiphase buffering range. This Perspective highlights the need for more comprehensive field observations under different conditions and further studies in the interactions among organic acids, acidity, and cloud chemistry.

Comparative multi-model study of PM2.5 acidity trend changes in ammonia-rich regions in winter: Based on a new ammonia concentration assessment method

Air quality in ammonia-rich regions such as Zhengzhou is improving year by year, however, fine particulate matter (PM_2.5) pollution is serious in winter. Aerosol acidity (pH) affects every aspect of the surrounding particle composition and environment. Thermodynamic models of gaseous and particulate composition datasets can provide pH estimates. Nevertheless, for ammonia-rich regions in the presence of prolonged NH₃ deficiency, the thermodynamic model is limited in calculating pH by using only datasets composed of the particulate phase. In this study, an NH₃ concentration calculation method was established via SPSS-coupled multiple linear regression to simulate the trend of NH₃ concentration over a long period of time and to assess the long-term pH value in ammonia-rich regions. The reliability of this method was verified using multiple models. The range of NH₃ concentration change from 2013 to 2020 was found to be 4.3-68.6 μg·m^-3, and the range of pH change was 4.5-6.0. The pH sensitivity analysis indicated that decreasing aerosol precursor concentrations and variations in temperature and relative humidity were the driving factors for aerosol pH changes. Therefore, policies to reduce NH₃ emissions are becoming increasingly necessary. This study provides a feasibility analysis for reducing PM_2.5, thus achieving standards in ammonia-rich regions, including Zhengzhou.

Dust emission reduction enhanced gas-to-particle conversion of ammonia in the North China Plain

Ammonium salt is an important component of particulate matter with aerodynamic diameter less than 2.5 µm (PM_2.5) and has significant impacts on air quality, climate, and natural ecosystems. However, a fundamental understanding of the conversion kinetics from ammonia to ammonium in unique environments of high aerosol loading is lacking. Here, we report the uptake coefficient of ammonia (γ_NH3) on ambient PM_2.5 varying from 2.2 × 10^-4 to 6.0 × 10^-4 in the North China Plain. It is significantly lower than those on the model particles under simple conditions reported in the literature. The probability-weighted γ_NH3 increases obviously, which is well explained by the annual decrease in aerosol pH due to the significant decline in alkali and alkali earth metal contents from the emission source of dust. Our results elaborate on the complex interactions between primary emissions and the secondary formation of aerosols and the important role of dust in atmospheric chemistry.

Aerosol pH and Ion Activities of HSO4- and SO42- in Supersaturated Single Droplets

Accurate determination of acidity (pH) and ion activities in aqueous droplets is a major experimental and theoretical challenge for understanding and simulating atmospheric multiphase chemistry. Here, we develop a ratiometric Raman spectroscopy method to measure the equilibrium concentration of sulfate (SO₄^2-) and bisulfate (HSO₄^-) in single microdroplets levitated by aerosol optical tweezers. This approach enables determination of ion activities and pH in aqueous sodium bisulfate droplets under highly supersaturated conditions. The experimental results were compared against aerosol thermodynamic model calculations in terms of simulating aerosol ion concentrations, ion activity coefficients, and pH. We found that the Extended Aerosol Inorganics Model (E-AIM) can well reproduce the experimental results. The alternative model ISORROPIA, however, exhibits substantial deviations in SO₄^2- and HSO₄^- concentrations and up to a full unit of aerosol pH under acidic conditions, mainly due to discrepancies in simulating ion activity coefficients of SO₄^2--HSO₄^- equilibrium. Globally, this may cause an average deviation of ISORROPIA from E-AIM by 25 and 65% in predicting SO₄^2- and HSO₄^- concentrations, respectively. Our results show that it is important to determine aerosol pH and ion activities in the investigation of sulfate formation and related aqueous phase chemistry.

Direct measurement of the pH of aerosol particles using carbon quantum dots

The pH of aerosol particles remains challenging to measure because of their small size, complex composition, and high acidity. Acidity in aqueous aerosol particles, which are found abundantly in the atmosphere, impacts many chemical processes from reaction rates to cloud formation. Only one technique - pH paper - currently exists for directly determining the pH of aerosol particles, and this is restricted to measuring average acidity for entire particle populations. Other methods for evaluating aerosol pH include filter samples, particle-into-liquid sampling, Raman spectroscopy, organic dyes, and thermodynamic models, but these either operate in a higher pH range or are unable to assess certain chemical species or complexity. Here, we present a new method for determining acidity of individual particles and particle phases using carbon quantum dots as a novel in situ fluorophore. Carbon quantum dots are easily synthesized, shelf stable, and sensitive to pH in the highly acidic regime from pH 0 to pH 3 relevant to ambient aerosol particles. To establish the method, a calibration curve was formed from the ratiometric fluorescence intensity of aerosolized standard solutions with a correlation coefficient (R²) of 0.99. Additionally, the pH of aerosol particles containing a complex organic mixture (COM) representative of environmental aerosols was also determined, proving the efficacy of using carbon quantum dots as pH-sensitive fluorophores for complex systems. The ability to directly measure aerosol particle and phase acidity in the correct pH range can help parametrize atmospheric models and improve projections for other aerosol properties and their influence on health and climate.

Targeting Atmospheric Oxidants Can Better Reduce Sulfate Aerosol in China: H2O2 Aqueous Oxidation Pathway Dominates Sulfate Formation in Haze

Particulate sulfate is one of the most important components in the atmosphere. The observation of rapid sulfate aerosol production during haze events provoked scientific interest in the multiphase oxidation of SO₂ in aqueous aerosol particles. Diverse oxidation pathways can be enhanced or suppressed under different aerosol acidity levels and high ionic strength conditions of atmospheric aerosol. The importance of ionic strength to sulfate multiphase chemistry has been verified under laboratory conditions, though studies in the actual atmosphere are still limited. By utilizing online observations and developing an improved solute strength-dependent chemical thermodynamics and kinetics model (EF-T&K model, EF is the enhancement factor that represents the effect of ionic strength on an aerosol aqueous-phase reaction), we provided quantitative evidence that the H₂O₂ pathway was enhanced nearly 100 times and dominated sulfate formation for entire years (66%) in Tianjin (a northern city in China). TMI (oxygen catalyzed by transition-metal ions) (14%) and NO₂ (14%) pathways got the second-highest contributions. Machine learning supported the result that aerosol sulfate production was more affected by the H₂O₂ pathway. The collaborative effects of atmospheric oxidants and SO₂ on sulfate aerosol production were further investigated using the improved EF-T&K model. Our findings highlight the effectiveness of adopting target oxidant control as a new direction for sustainable mitigation of sulfate, given the already low SO₂ concentrations in China.

Multiphase buffer theory explains contrasts in atmospheric aerosol acidity

Aerosol acidity largely regulates the chemistry of atmospheric particles, and resolving the drivers of aerosol pH is key to understanding their environmental effects. We find that an individual buffering agent can adopt different buffer pH values in aerosols and that aerosol pH levels in populated continental regions are widely buffered by the conjugate acid-base pair NH4+/NH3 (ammonium/ammonia). We propose a multiphase buffer theory to explain these large shifts of buffer pH, and we show that aerosol water content and mass concentration play a more important role in determining aerosol pH in ammonia-buffered regions than variations in particle chemical composition. Our results imply that aerosol pH and atmospheric multiphase chemistry are strongly affected by the pervasive human influence on ammonia emissions and the nitrogen cycle in the Anthropocene.

A quantitative analysis of the driving factors affecting seasonal variation of aerosol pH in Guangzhou, China

Aerosol acidity is of great interest due to its effects on atmospheric chemical processes and impact on human health; however, the driving factors of aerosol acidity have only been scarcely investigated. This study characterized the aerosol acidity during the wet and dry seasons in Guangzhou, China, and systematically analyzed the seasonal variation and the corresponding driving factors of aerosol acidity followed by the discussion of their impact on gas-aerosol partitioning of NH₃ and HNO₃. It was demonstrated that the pH of PM_2.5 was 0.08 unit lower (more acidic) during wet season than during the dry season and the aerosol acidity varied less in South China than that in North China. Additionally, our results showed that the meteorological parameters including temperature and relative humidity have larger effect on aerosol pH variation than chemical species. Particularly, the lower temperature during dry season had the positive influence (0.38 pH unit) on aerosol pH compared to the wet season; however, the negative effect due to relative humidity (RH) and chemical species resulted in a smaller seasonal variation of aerosol pH between these two seasons. The sensitivity analysis showed that the increase of temperature has negative impact (reducing pH) on aerosol pH with an almost linear relationship, while RH and chemical species represented a two-phase linear and nonlinear effect, respectively. Finally, the calculation of gas-aerosol partitioning indicated that the temperature had the largest influence on the seasonal variation of gas-aerosol partitioning for both HNO₃ and NH₃ followed by liquid water content and non-ideality, while aerosol acidity imposed the lowest impact, which suggests that all the parameters including meteorological and chemical species should be comprehensively evaluated to devise a PM_2.5 control strategy.