Atmospheric emissions of particulate matter-bound heavy metals from industrial sources.

Although industrial activities are significant contributors to atmospheric releases of particulate matter (PM) and associated toxic substances that lead to adverse human health effects, a knowledge gap exists concerning the human health risk resulting from such activities owing to lack of evaluation of industrial emissions. Here, we comprehensively characterized and quantified PM from 118 full-scale industrial plants. The dominant (97.9 %) PM showed diameters of <2.5 µm; 79.0 % had diameters below 1 µm. Annual atmospheric releases of Fe and heavy metals (As, Cd, Cr, Cu, Ni, Pb, Zn) contained in fine PM from these global industrial activities are estimated to be 51,161 t and 69,591 t, respectively. Emissions of heavy metals from these industries cause increased cancer risk, estimated to range from 1461 % to 50,752 %. Five crystalline compounds (ZnO, PbSO4, Mn3O4, Fe3O4, Fe2O3) that can indicate specific industrial sources are identified. Global annual emissions of these toxic compounds in fine PM from the industrial sources are estimated to be 78,635 t. The Global South displayed higher emissions than the Global North. These results are significant for recognizing regional health risks of industrial emissions.

Atmospheric emissions of hexachlorobutadiene in fine particulate matter from industrial sources.

Hexachlorobutadiene (HCBD) is a concerning chemical that is included in the United States Toxic Substances Control Act, and the Stockholm Convention. Knowledge of the sources of HCBD is insufficient and is pivotal for accurate inventory and implementing global action. In this study, unintentional HCBD release and source emission factors of 121 full-scale industrial plants from 12 industries are investigated. Secondary copper smelting, electric arc furnace steelmaking, and hazardous waste incineration show potential for large emission reductions, which are found of high HCBD emission concentrations of > 20 ng/g in fine particulate matter in this study. The highest HCBD emission concentration is observed for the secondary copper smelting industry (average: 1380 ng/g). Source emission factors of HCBD for the 12 industries range from 0.008 kg/t for coal fire power plants to 0.680 kg/t for secondary lead smelting, from which an estimation of approximately 8452.8 g HCBD emissions annually worldwide achieved. The carcinogenic risks caused by HCBD emissions from countries and regions with intensive 12 industrial sources are 1.0-80 times higher than that without these industries. These results will be useful for formulating effective strategies of HCBD control.

Diagnosis of cervical lymphoma using a YOLO-v7-based model with transfer learning.

To investigate the ability of an auxiliary diagnostic model based on the YOLO-v7-based model in the classification of cervical lymphadenopathy images and compare its performance against qualitative visual evaluation by experienced radiologists. Three types of lymph nodes were sampled randomly but not uniformly. The dataset was randomly divided into for training, validation, and testing. The model was constructed with PyTorch. It was trained and weighting parameters were tuned on the validation set. Diagnostic performance was compared with that of the radiologists on the testing set. The mAP of the model was 96.4% at the 50% intersection-over-union threshold. The accuracy values of it were 0.962 for benign lymph nodes, 0.982 for lymphomas, and 0.960 for metastatic lymph nodes. The precision values of it were 0.928 for benign lymph nodes, 0.975 for lymphomas, and 0.927 for metastatic lymph nodes. The accuracy values of radiologists were 0.659 for benign lymph nodes, 0.836 for lymphomas, and 0.580 for metastatic lymph nodes. The precision values of radiologists were 0.478 for benign lymph nodes, 0.329 for lymphomas, and 0.596 for metastatic lymph nodes. The model effectively classifies lymphadenopathies from ultrasound images and outperforms qualitative visual evaluation by experienced radiologists in differential diagnosis.

Development, Validation, and Comparison of 2 Ultrasound Feature-Guided Machine Learning Models to Distinguish Cervical Lymphadenopathy.

ABSTRACT: The objective of this study is to develop and validate the performance of 2 ultrasound (US) feature-guided machine learning models in distinguishing cervical lymphadenopathy. We enrolled 705 patients whose US characteristics of lymph nodes were collected at our hospital. B-mode US and color Doppler US features of cervical lymph nodes in both cohorts were analyzed by 2 radiologists. The decision tree and back propagation (BP) neural network were developed by combining clinical data (age, sex, and history of tumor) and US features. The performance of the 2 models was evaluated by calculating the area under the receiver operating characteristics curve (AUC), accuracy value, precision value, recall value, and balanced F score (F1 score). The AUC of the decision tree and BP model in the modeling cohort were 0.796 (0.757, 0.835) and 0.854 (0.756, 0.952), respectively. The AUC, accuracy value, precision value, recall value, and F1 score of the decision tree in the validation cohort were all higher than those of the BP model: 0.817 (0.786, 0.848) vs 0.674 (0.601, 0.747), 0.774 (0.737, 0.811) vs 0.702 (0.629, 0.775), 0.786 (0.739, 0.833) vs 0.644 (0.568, 0.720), 0.733 (0.694, 0.772) vs 0.630 (0.542, 0.718), and 0.750 (0.705, 0.795) vs 0.627 (0.541, 0.713), respectively. The US feature-guided decision tree model was more efficient in the diagnosis of cervical lymphadenopathy than the BP model.

Comprehensive Evaluation of Dietary Exposure and Health Risk of Polychlorinated Naphthalenes.

Intake from food is considered an important route of human exposure to polychlorinated naphthalenes. To our knowledge, several studies have quantified dietary exposure but only in European countries and measuring only a few of the 75 congeners. In addition, the influence of source diversity on human exposure has seldom been assessed. We analyzed 192 composite food samples composed of 17,280 subsamples from 24 provinces in China to measure the concentrations of polychlorinated naphthalenes and estimate their daily intake and potential health risks on a national scale. The estimated cancer risk was in the range of 6.8 × 10-8 to 4.6 × 10-7. We compared our findings for 75 congeners with reports in the literature that quantified only 12 congeners. We estimate that these 12 congeners contribute only approximately 4% to the total mass daily intake of polychlorinated naphthalenes and 70% to the total toxic equivalent quantity, indicating underestimation of dietary exposure. The contributions of combustion-associated congeners to the total concentrations of polychlorinated naphthalenes were in the range of 31-52%, suggesting that the ongoing unintentional release of these compounds from industrial thermal processes is an important factor in polychlorinated naphthalene contamination and human exposure in China.

Occurrence of chlorinated and brominated polycyclic aromatic hydrocarbons from electric arc furnace for steelmaking.

Chlorinated and brominated polycyclic aromatic hydrocarbons (Cl/Br-PAHs) are persistent organic pollutants with potential carcinogenic toxicities that are even higher than those of their parent PAH congeners. Current knowledge of Cl/Br-PAH sources and emission characteristics is lacking. Electric arc furnace (EAF) steelmaking is a potential source for Cl/Br-PAHs, considering that preheating of raw materials before they enter the EAF could produce suitable conditions for Cl/Br-PAHs formation. In this field study, we identified EAFs as an important source of Cl/Br-PAHs and clarified their emission concentrations, fingerprints by gas chromatography coupled with high-resolution magnetic mass spectrometry. Potential formation mechanisms of Cl/Br-PAHs were also proposed. The mass concentration ranges for Σ18Cl-PAHs and Σ18Br-PAHs in stack gas were 25.85-4191 ng Nm-3 and 1.02-341 ng Nm-3, respectively. The variation of concentration indicated that the steel scrap composition greatly affected the production of Cl/Br-PAHs. The congener ratios including 6-chlorobenzo [a]pyrene/3-chlorofluoranthene and 1-chloroanthracene/1-chloropyrene could be used to estimate the influence of industrial sources on Cl-PAH occurrences in the air. Ring structure growth was the dominant formation pathway for Cl/Br-PAHs, distinctly different from dioxin formation mechanisms dominated by precursor dimerization and chlorination.

Characterizing the emissions of polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs) from electric arc furnaces during steel-making.

The amount of steel produced using electric arc furnaces (EAFs) has been increasing in recent years. In this study, stack gases from EAFs in steelmaking plants were analyzed to determine if they are also dominant sources of polybrominated dibenzo-p-dioxin and dibenzofuran (PBDD/F) emissions in China. Isotope dilution high-resolution gas chromatography high-resolution mass spectrometry for qualitative and quantitative analysis of PBDD/F congeners revealed that the mean PBDD/F mass concentrations were 271.1-9467.8 pg Nm-3 for the preheating stages (PS) of three EAF plants and that the corresponding toxic equivalents (TEQs) were 10.8-971.2 pg TEQ Nm-3. The PBDD/F mass concentration from the smelting stage (SS) at plant E3 was 261.9 pg Nm-3 (4.5 pg TEQ Nm-3). The PBDD/F emission factors (EF) during the preheating stage for the three plants were 0.0356-1.51 µg TEQ t-1, and the EF was 0.0359 µg TEQ t-1 during the E3 smelting stage. PBDD/Fs were found to contribute 2.39-67.85% to the total mass and 2.84-57.68% to the total dioxin TEQ. These wide fluctuations were caused by differences in the composition of feeding materials and the working temperature of bag filters. Overall, the results indicate that PBDD/F emissions from EAF steelmaking should receive increased attention. The PBDD/F congener patterns among the three EAF plants were variable, possibly because of differences in raw materials. The results presented herein will facilitate assessment of the contribution of EAFs to total PBDD/F emissions in China and investigations of PBDD/F emissions at different stages of steelmaking processes using EAFs.