Understanding the atmospheric fate of triphenylene: The oxidation mechanism initiated by OH radicals

Pollution Characterization and Environmental Impact Evaluation of Atmospheric Intermediate Volatile Organic Compounds: A Review

Atmospheric intermediate volatile organic compounds (IVOCs) are important precursors of secondary organic aerosols (SOAs), and in-depth research on them is crucial for atmospheric pollution control. This review systematically synthesizes global advancements in understanding IVOC sources, emissions characterization, compositional characteristics, ambient concentrations, SOA contributions, and health risk assessments. IVOCs include long-chain alkanes (C12~C22), sesquiterpenes, polycyclic aromatic hydrocarbons, monocyclic aromatic hydrocarbons, phenolic compounds, ketones, esters, organic acids, and heterocyclic compounds, which originate from primary emissions and secondary formation. Primary emissions include direct emissions from anthropogenic and biogenic sources, while secondary formation mainly results from radical reactions or particulate surface reactions. Recently, the total IVOC emissions have decreased in some countries, while emissions from certain sources, such as volatile chemical products, have increased. Ambient IVOC concentrations are generally higher in urban rather than in rural areas, higher indoors than outdoors, and on land rather than over oceans. IVOCs primarily generate SOAs via oxidation reactions with hydroxyl radicals, nitrate radicals, the ozone, and chlorine atoms, which contribute more to SOAs than traditional VOCs, with higher SOA yields. SOA tracers for IVOC species like naphthalene and β-caryophyllene have been identified. Integrating IVOC emissions into regional air quality models could significantly improve SOA simulation accuracy. The carcinogenic risk posed by naphthalene should be prioritized, while benzo[a]pyrene requires a combined risk assessment and hierarchical management. Future research should focus on developing high-resolution online detection technologies for IVOCs, clarifying the multiphase reaction mechanisms involved and SOA tracers, and conducting comprehensive human health risk assessments.

Identification and Prioritization of Organic Pollutants in Human Milk from the Yangtze River Delta, China

Pollutants in human milk are critical for evaluating maternal internal exposure and infant external exposure. However, most studies have focused on a limited range of pollutants. Here, 15 pooled samples (prepared from 467 individual samples) of human milk from three areas of the Yangtze River Delta (YRD) in China were analyzed by gas chromatography quadrupole time-of-flight mass spectrometry. In total, 171 compounds of nine types were preliminarily identified. Among these, 16 compounds, including 2,5-di-tert-butylhydroquinone and 2-tert-butyl-1,4-benzoquinone, were detected in human milk for the first time. Partial least-squares discriminant analysis identified ten area-specific pollutants, including 2-naphthylamine, 9-fluorenone, 2-isopropylthianthrone, and benzo[a]pyrene, among pooled human milk samples from Shanghai (n = 3), Jiangsu Province (n = 6), and Zhejiang Province (n = 6). Risk index (RI) values were calculated and indicated that legacy polycyclic aromatic hydrocarbons (PAHs) contributed only 20% of the total RIs for the identified PAHs and derivatives, indicating that more attention should be paid to PAHs with various functional groups. Nine priority pollutants in human milk from the YRD were identified. The most important were 4-tert-amylphenol, caffeine, and 2,6-di-tert-butyl-p-benzoquinone, which are associated with apoptosis, oxidative stress, and other health hazards. The results improve our ability to assess the health risks posed by pollutants in human milk.

Degradation of Azithromycin from aqueous solution using Chlorine-ferrous- oxidation: ANN-GA modeling and Daphnia magna biotoxicity test assessment

Azithromycin (AZM), an antibacterial considered one of the most consumed drugs, especially during the period against the Covid 19 pandemic, and it is one of the persistent contaminants that can be released into aquatic ecosystems. The purpose of this study is to determine the efficacy of a Fenton-like process (chlorine/iron) for the degradation of AZM in an aqueous medium by determining the impact of several factors (the initial concentration of (FeSO₄, NaClO, pollutant), and the initial pH) on the degradation rate. The Response Surface Methodology (RSM) based on the Box-Wilson design as well as the Artificial Neural Network (ANN) modeling combined with a genetic algorithm (GA) approaches were used to determine the optimal levels of the selected variables and the optimal rate of degradation. The quadratic model of multi-linear regression developed indicated that the optimal conditions were a concentration of chlorine of 600 μM, the concentration of AZM is 32.8 mg/L, the mass of the catalyst FeSO₄ is 3.5 mg and a pH of 2.5, these optimal values gave a predicted and experimental yield of 64.05% and 70% respectively, the lack of fit test in RSM modeling (F₀ = 3.31 which is inferior to Fcritic (0.05, 10.4) = 5.96) indicates that the true regression function is not linear therefore, the ANN-GA modeling as non-linear regression indicated that the optimal conditions were a concentration of chlorine of 256 μM, the concentration of AZM is 5 mg/L, the mass of the catalyst FeSO₄ is 9.5 mg and a pH of 2.8, these optimal values gave a predicted and experimental yield of 79.69% and close to 80% respectively, Furthermore, biotoxicity tests were conducted to confirm the performance of our process using bio-indicators called daphnia (Daphnia magna), which demonstrated the efficacy of the like-Fenton process after 4 h of degradation.