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Ingestion of perfluoroalkyl acids (PFAAs) via contaminated food contact materials (FCMs) is an important human exposure source. This study adopts a toxicity equivalent approach to evaluate the collective health risk of multiple PFAAs in FCMs. A comprehensive extraction and analysis of 21 PFAAs in FCMs was performed. Among the analyzed substances, 15 PFAAs were detected. Migration experiment using three food simulants revealed the migration range of seven PFAAs from FCMs into the simulant to be 0.47–46.7 ng/cm2. The hazard quotient results suggest minimal health risk, except for 9% of packaged samples where perfluorooctanoic acid (PFOA) poses a higher risk. Utilizing PFOA toxic equivalent concentrations, comprehensive risk calculations showed ∼77% of samples potentially posing elevated health risks due to PFAA exposure. This emphasizes the substantial contribution of PFAAs beyond PFOA and underscores the importance of considering them in related assessments. The aggregated risk assessment reflects actual exposure circumstances more accurately. [ABSTRACT FROM AUTHOR]

Taiyuan in the Shanxi Province of China has experienced significant air pollution from fine particulate matter (PM2.5) in the past years. Phthalate esters (PAEs), which are common semi-volatile chemical molecules in PM2.5 and that humans can breathe into their bodies, can have serious health consequences. This study looked at the levels, composition, sources, and incremental lifetime lung cancer risk factors for PM2.5-bound PAEs in Taiyuan. A QuEChERS extraction technique and gas chromatography-tandem mass spectrometry were used to evaluate 16 PAE compounds. All samples contained PAEs, and the overall PAE concentration ranged from 114 to 864 ng/m3. The most often detected compound was bis(2-ethylhexyl)phthalate (DEHP), and summer PAE concentrations were substantially greater than winter ones. A positive matrix factorization model showed that the main sources of PAE release were the indoor environment, industry source, automobile-related source, and construction source. The places within 300 km of Taiyuan were thought to have a significant impact on PAEs, according to the analysis of the prospective source contribution function. The calculated incremental lifetime lung cancer risk of DEHP exposure was 0.76 cases per million people. More of the risk of lung cancer has been attributed to indoor air pollution (53.2%). These findings will help us understand the features of PAE contamination and offer a solid scientific foundation for minimizing PAE pollution in the Loess Plateau. [ABSTRACT FROM AUTHOR]

Rapid and accurate prediction of river water quality is an important task of urban water management strategy. However, River water quality factors have the characteristics of time series, instability, and nonlinearity, and are affected by many factors, which will cause differences in spatial and temporal dimensions. Most of the existing water quality factor forecasting methods are time series forecasting at a single monitoring station, which cannot describe the spatial distribution of river water quality factors. In this paper, we proposes a spatiotemporal prediction model of river water quality (STG-LSTM) on account of spatio-temporal graph convolution and long-short-term memory neural network. Based on the historical observation values of the geographic location and water quality factors of each monitoring station, construct a time-space map to characterize the time-space correlation between each monitoring station. Input the space-time diagram into the STG-LSTM model, using graph convolution (GCN) to obtain the spatial dependence of river water quality factor data and fusing the long and short-term memory neural network (LSTM) to obtain the spatio-temporal correlation of the water quality factor data, we realized the future period temporal and spaltial prediction of water quality at different locations in the canal section. The data sets of four different water quality factors at eight monitoring stations on the Changzhou section of the Beijing-Hangzhou Canal were used for verification. The model was compared with six other prediction models in terms of prediction accuracy and training time, and the reliability of the model was tested. The experimental results show that STG-LSTM can obtain high prediction accuracy with a short training time and realize rapid and accurate prediction of water quality at different locations of the river. Most but not the least, they provide technical support for urban water management. [ABSTRACT FROM AUTHOR]