Anthropogenic Emission Sources of Sulfate Aerosols in Hangzhou, East China: Insights from Isotope Techniques with Consideration of Fractionation Effects between Gas-to-Particle Transformations

Significantly surfactant-enhanced photochemical conversion of SO2 to sulfates on photosensitive substances

The photochemical conversion of SO2 to sulfates on 4-(benzoyl) benzoic acid (4-BBA) was investigated deeply in the presence of anionic and cationic surfactants. The types of surfactants determined their effect behaviors, and cationic surfactants can significantly enhance the SO2 oxidation on 4-BBA under irradiation, as shown by larger SO2 uptake coefficients and sulfate production. Hydrophilic moieties in cationic surfactants have a greater enhancement effect on the photochemical conversion of SO2 to sulfates than the corresponding hydrophobic moieties. Cationic surfactants obviously increased the accumulation of H2O on the surface, which was proved to be the main factor influencing the SO2 uptake and the sulfate formation on 4-BBA. SO2 lifetime and sulfate formation rate in the mixture system of photosensitive substances with surfactants were evaluated to be 2.25 days and 0.09 µg/(m3·h), respectively.

NO2-promoted heterogeneous photochemical oxidation of SO2 to sulfates on brown carbon

The role of NO2 in the heterogeneous photochemical formation of sulfates by SO2 uptake on typical brown carbon (BrC) species (Fluoranthene, FL; 4-(benzoyl) benzoic acid, 4-BBA; 3,7-dihydroxy-2-naphthoic acid, 3,7-DHNA) was systemically explored in a flow tube reactor with the infrared spectroscopy, ion chromatography as well as theoretical calculation. NO2 enhanced SO2 uptake and sulfate generation on BrC under irradiation, as shown by larger steady-state uptake coefficients of SO2 and sulfate formation rates. NO2- can be produced through the reduction of NO2 by the photogenerated electrons on BrC, and it was proven to be the trigger that promoted the oxidation of SO2 to sulfates. NO2- was more easily formed on FL, followed by 4-BBA and 3,7-DHNA, which can be evidenced by the energy barrier for NO2- production: FL (0.01 kJ mol-1) < 4-BBA (0.12 kJ mol-1) < 3,7-DHNA (1.33 kJ mol-1). SO2 lifetimes and sulfate formation rates during the reaction of SO2/NO2 with BrC were estimated to be 10.60-31.75 days and 0.02-0.04 μg m-3 h-1, respectively.

Advancing Source Apportionment of Atmospheric Particles: Integrating Morphology, Size, and Chemistry Using Electron Microscopy Technology and Machine Learning

To further reduce atmospheric particulate matter concentrations, there is a need for a more precise identification of their sources. The SEM-EDS technology (scanning electron microscopy and energy-dispersive X-ray spectroscopy) can provide high-resolution imaging and detailed compositional analysis for particles with relatively stable physical and chemical properties. This study introduces an advanced source apportionment pipeline (RX model) that uniquely combines computer-controlled scanning electron microscopy with computer vision and machine learning to trace particle sources by integrating single-particle morphology, size, and chemical information. In the evaluation using a virtual data set with known source contributions, the RX model demonstrated high accuracy, with average errors of 0.60% for particle number and 1.97% for mass contribution. Compared to the chemical mass balance model, the RX model's accuracy and stability improved by 75.6 and 73.4%, respectively, and proved effective in tracing Fe-containing particles in the atmosphere of a steel city in China. This study indicates that particle morphology can serve as an effective feature for determining its source. The findings highlight the potential of electron microscopy technology coupled with computer vision and machine learning techniques to enhance our understanding of atmospheric pollution sources, offering valuable insights for PM health risk assessment and evidence-based policy-making.

In situ biomass burning enhanced the contribution of biogenic sources to sulfate aerosol in subtropical cities

Sulfurous gases released by biogenic sources play a key role in the global sulfur cycle. However, the contribution of biogenic sources to sulfate aerosol in the urban atmosphere has received little attention. Emission sources and formation process of sulfate in Guangzhou, a subtropical mega-city in China, were clarified using multiple methods, including isotope tracers and chemical markers. The δ18O of sulfate suggested that secondary sulfate was the dominant component (84 %) of sulfate aerosol, which mainly formed by transition metal ion (TMI) catalyzed oxidation (31 %) and OH radical oxidation (30 %). The factors driving secondary sulfate formation were revealed using a tree boosting model, which suggested that NH3, temperature, and oxidants were the most important factors. The δ34S of sulfate indicated that biogenic sources accounted for annual average of 26.0 % of the sulfate, which increased to 30.4 % in winter monsoon period. Rice straw burning enhanced sulfate formation by promoting the release of reduced sulfur from soil, which is rapidly converted into sulfate under a subtropical urban atmosphere with high concentration of NH3 and oxidants. This study revealed the important influence of rice straw burning on biogenic sulfur emission during the rice harvest, thereby providing insight into the sulfur cycle and regional air pollution.

Sulfur isotope-based source apportionment and control mechanisms of PM2.5 sulfate in Seoul, South Korea during winter and early spring (2017-2020)

High level of particulate matter (PM) concentrations are a major environmental concern in Seoul, South Korea, especially during winter and early spring. Sulfate is a major component of PM and induces severe environmental pollution, such as acid precipitation. Previous studies have used numerical models to constrain the relative contributions of domestic and trans-boundary sources to PM2.5 sulfate concentration in South Korea. Because of the scarce measurement result of δ34S for PM2.5 sulfate in South Korea, poorly defined δ34S value of domestic sulfur sources, and no application of sulfur isotope fractionation during sulfate formation in previous observation-based studies, source apportionment results conducted by model studies have not been corroborated from independent chemical observations. Here, we examined the δ34S of PM2.5 in Seoul and domestic sulfur sources, and considered the sulfur isotope fractionation for accurate source apportionment constraint. Accordingly, domestic and trans-boundary sulfur sources accounted for approximately (16-32) % and (68-84) % of the sulfate aerosols in Seoul, respectively, throughout the winter and early spring of 2017-2020. Air masses passing through north-eastern China had relatively low sulfate concentrations, enriched δ34S, and a low domestic source contribution. Those passing through south-eastern China had relatively a high sulfate concentrations, depleted δ34S, and high domestic source contribution. Furthermore, elevated PM2.5 sulfate concentrations (>10 μg m-3) were exclusively associated with a weak westerly wind speed of <3 m s-1. From December 2019 to March 2020, Seoul experienced relatively low levels of PM2.5 sulfate, which might be attributed to favorable weather conditions rather than the effects of COVID-19 containment measures. Our results demonstrate the potential use of δ34S for accurate source apportionment and for identifying the crucial role of regional air mass transport and meteorological conditions in PM2.5 sulfate concentration. Furthermore, the data provided can be essential for relevant studies and policy-making in East Asia.

Temporal and spatial shifts in the chemical composition of urban coastal rainwaters of Kuwait: The role of air mass trajectory and meteorological variables

The rainwater chemistry encompasses the signatures of geogenic and anthropogenic processes along the regional air mass movement apart from the local sources. The predominance of dust events and anthropogenic emissions in arid regions facilitate new particle formation. Further, rain events of different seasons depict moisture sources from diverse regions reflecting variation in the regional geochemistry with respect to seasons. Hence, to characterize the geochemical composition of rainwater, the study has focused on an integrated approach by considering regional transport, meteorological components and possible local sources. A total of 74 rainwater samples were collected from 27 rain events in 2018, 2019, and 2022, representing urban coastal areas of Kuwait predominantly of Ca-SO4-HCO3 type. The average pH and electrical conductivity of the rainwater were 7.18 and 140 μS/cm, respectively. The sea salt fractions calculated relative to Kuwait seawater ranged from 25.6 to >100 %, with higher values attributed to anthropogenic sources. Sea salt fraction, ion ratios, principal component analysis and factor scores revealed the terrestrial and anthropogenic sources apart from marine contributions. In addition, new particle formation and aerosols contributed to the rainwater chemistry involving SOx, NOx, and photochemical reactions during higher relative humidity and lesser wind speed. The HYSPLIT reflected that the moisture sources were largely from western regions of the study area, and those of December and January events had long-distance travel across the Azores high originating from northeast America. The trajectories of the November events are observed to originate from the Caspian/Black Sea region in the northeastern part of Kuwait with a relatively shorter distance of travel. The rainfall samples had higher ionic concentrations, and saturated with aragonite and calcite minerals in a few locations specifically after the dust events, while the subsequent rain events were less polluted.

An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species

Previous studies have determined biomass burning as a major source of air pollutants in the ambient air in Thailand. To analyse the impacts of meteorological parameters on the variation of carbonaceous aerosols and water-soluble ionic species (WSIS), numerous statistical models, including a source apportionment analysis with the assistance of principal component analysis (PCA), hierarchical cluster analysis (HCA), and artificial neural networks (ANNs), were employed in this study. A total of 191 sets of PM2.5 samples were collected from the three monitoring stations in Chiang-Mai, Bangkok, and Phuket from July 2020 to June 2021. Hotspot numbers and other meteorological parameters were obtained using NOAA-20 weather satellites coupled with the Global Land Data Assimilation System. Although PCA revealed that crop residue burning and wildfires are the two main sources of PM2.5, ANNs highlighted the importance of wet deposition as the main depletion mechanism of particulate WSIS and carbonaceous aerosols. Additionally, Mg2+ and Ca2+ were deeply connected with albedo, plausibly owing to their strong hygroscopicity as the CCNs responsible for cloud formation.