Multi isotope systematics of precipitation to trace the sources of air pollutants in Seoul, Korea

Procedures from samples to sulfur isotopic data: A review

RATIONALE

Sulfur isotopes have been widely used to solve some key scientific questions, especially in the last two decades with advanced instruments and analytical schemes. Different sulfur speciation and multiple isotopes analyzed in laboratories worldwide and in situ microanalysis have also been reported in many articles. However, methods of sampling to measurements are multifarious, and occasionally some inaccuracies are present in published papers. Vague methods may mislead newcomers to the field, puzzle readers, or lead to incorrect data-based correlations.

METHODS

We have reviewed multiple methods on sulfur isotopic analyses from the perspectives of sampling, laboratory work, and instrumental analysis in order to help reduce operational inhomogeneity and ensure the fidelity of sulfur isotopic data. We do not deem our proposed solutions as the ultimate standard methods but as a lead-in to the overall introduction and summary of the current methods used.

RESULTS

It has been shown that external contamination and transformation of different sulfur species should be avoided during the sampling, pretreatment, storage, and chemical treatment processes. Conversion rates and sulfur isotopic fractionations during sulfur extraction, purification, and conversion processes must be verified by researchers using standard or known samples. The unification of absence of isotopic fractionation is needed during all steps, and long-term monitoring of standard samples is recommended.

CONCLUSION

This review compiles more details on different methods in sampling, laboratory operation, and measurement of sulfur isotopes, which is beneficial for researchers' better practice in laboratories. Microanalyses and molecular studies are the frontier techniques that compare the bulk sample with the elemental analysis/continuous flow-gas source stable isotope ratio mass spectrometry method, but the latter is widely used. The development of sulfur isotopic measurements will lead to the innovation in scientific issues with sulfur proxies.

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.

Nitrate dynamics and source identification of rainwater in Beijing during rainy season: Insight from dual isotopes and Bayesian model

Anthropogenic reactive nitrogen emissions have a significant impact on atmospheric chemical composition and earth surface ecosystem. As one of the most important sinks of atmospheric nitrogen, the wet deposition of nitrate (rainwater NO₃^-) has been widely concerned. Yet, the sources and transformation processes of wet deposited NO₃^- were not well revealed in megacity during rainy season in the context of global climate change. Here, we investigated the concentrations of nitrogen components and dual isotopes of rainwater nitrate collected in Beijing during July to August 2021 (rainy season). The main findings showed that the concentrations of NH₄⁺-N, NO₃^--N, and NO₂^--N ranged 0.5- 6.7 mg L^-1, 0.3- 4.5 mg L^-1, and 0.05- 0.18 mg L^-1, respectively, with the average relative percentages of 69 %, 29 %, and 2 %. The stoichiometry analysis of characteristic ion ratios indicated that the contribution of municipal wastes and agricultural sources to rainwater NH₄⁺-N is relatively significant, while traffics were the major contributor of NO₃^--N instead of the fixed emission. Rainwater δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- presented slightly ¹⁵N-depleted characteristic compared to previous studies with the average values of -3.9 ± 3.1 ‰ and 58.7 ± 12.6 ‰. These isotope compositions suggesting an origin of rainwater NO₃^- from the mixing of multi-sources and was mainly generated via the pathway of OH radical oxidization. Further source apportionment of rainwater NO₃^- by Bayesian mixing model evaluated that traffic (30.3 %) and soil (30.3 %) emissions contributed mostly to NO₃^-, while the contribution of biomass burning (18.8 %) and coal combustion (20.6 %) were relatively lower. This study highlighted the important role of dual isotopes in rainwater nitrate source identification and formation processes in megacity.

Nitrate sources and its formation in precipitation during typhoons (In-fa and Chanthu) in multiple cities, East China

A clear understanding of the factors governing dual isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) in typhoons is essential for understanding their NO₃^- sources and its formation mechanisms. In this study, sequential precipitation samples during typhoons, including In-fa and Chanthu, were collected from Ningbo, Hangzhou and Huzhou. The chemical compositions, nitrogen and oxygen isotopes of NO₃^- and oxygen isotopes of H₂O (δ¹⁸O-H₂O) were measured. The results showed that the δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- values ranged from -6.3‰ to 6.0‰, and 38.0‰ to 66.5‰, respectively. The lower δ¹⁸O-NO₃^- values (less than 52‰) indicated the importance of peroxy radicals (RO₂ or HO₂) in NO_x oxidation to NO₃^- formation pathways. By the Monte Carlo simulation of δ¹⁸O-NO₃^- values of typhoons, the calculated oxidation proportions of NO by RO₂ (or HO₂) during the OH· pathway ranged from 0% to 27% of In-fa and from 0% to 32% of Chanthu, respectively, in the three cities. More NO_x emissions from marine microbial processes caused the lower δ¹⁵N-NO₃^- values of typhoons in Ningbo than those in Hangzhou and Huzhou. The variation in δ¹⁵N-NO₃^- values in sequential samples in In-fa reflected the decreased marine sources (lightning) and the increased anthropogenic sources in land (coal combustion and microbial N cycle) from Phrase I to Phrase II and III. Based on the improved Bayesian model with nitrogen isotopic fractionation, the contributions of lightning + biomass burning, coal combustion, mobile sources and the microbial N cycle were 35.7%, 22.5%, 27.1% and 14.7% in In-fa, and 28.3%, 32.3%, 28.0% and 11.4% in Chanthu, respectively, in the three cities, emphasizing the influence of marine NO_x sources (lightning). The results highlight the importance of RO₂ (or HO₂) in NO_x oxidation pathways in typhoons and provide valuable insight into the NO_x sources of typhoons.

Risk Assessment and Prediction of Air Pollution Disasters in Four Chinese Regions

Evaluating the regional trends of air pollution disaster risk in areas of heavy industry and economically developed cities is vital for regional sustainable development. Until now, previous studies have mainly adopted a traditional weighted comprehensive evaluation method to analyze the air pollution disaster risk. This research has integrated principal component analysis (PCA), a genetic algorithm (GA) and a backpropagation (BP) neural network to evaluate the regional disaster risk. Hazard risk, hazard-laden environment sensitivity, hazard-bearing body vulnerability and disaster resilience were used to measure the degree of disaster risk. The main findings were: (1) the air pollution disaster risk index of Liaoning Province, Beijing, Shanghai and Guangdong Province increased year by year from 2010 to 2019; (2) the mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) of each regional air pollution disaster risk index in 2019, as predicted by the PCA-GA-BP neural network, were 0.607, 0.317 and 20.3%, respectively; (3) the predicted results were more accurate than those using a PCA-BP neural network, GA-BP neural network, traditional BP neural network, support vector regression (SVR) or extreme gradient boosting (XGBoost), which verified that machine learning could be used as a method of air pollution disaster risk assessment to a considerable extent.