Trophic transfer of antibiotics in the benthic-pelagic coupling foodweb in a macrophyte-dominated shallow lake: The importance of pelagic-benthic coupling strength and baseline organism.

In lake ecosystems, pelagic-benthic coupling strength (PBCS) is closely related to foodweb structure and pollutant transport. However, the trophic transfer of antibiotics in a benthic-pelagic coupling foodweb (BPCFW) and the manner in which PBCS influences the trophic magnification factor (TMFs) of antibiotics is still not well understood in the whole lake. Herein, the trophic transfer behavior of 12 quinolone antibiotics (QNs) in the BPCFW of Baiyangdian Lake were studied during the period of 2018-2019. It was revealed that 24 dominant species were contained in the BPCFW, and the trophic level was 0.42-2.94. Seven QNs were detected in organisms, the detection frequencies of ofloxacin (OFL), flumequine (FLU), norfloxacin (NOR), and enrofloxacin (ENR) were higher than other QNs. The ∑QN concentration in all species was 11.3-321 ng/g dw. The TMFs for ENR and NOR were trophic magnification, while for FLU/OFL it was trophic dilution. The PBCS showed spatial-temporal variation, with a range of 0.6977-0.7910. The TMFs of ENR, FLU, and OFL were significantly positively correlated with PBCS. Phytoplankton and macrophyte biomasses showed indirect impact on the TMFs of QNs by directly influencing the PBCS. Therefore, the PBCS was the direct influencing factor for the TMFs of chemicals.

Research on joint model relation extraction method based on entity mapping.

Relationship Extraction (RE) is a central task in information extraction. The use of entity mapping to address complex scenarios with overlapping triples, such as CasRel, is gaining traction, yet faces challenges such as inadequate consideration of sentence continuity, sample imbalance and data noise. This research introduces an entity mapping-based method CasRelBLCF building on CasRel. The main contributions include: A joint decoder for the head entity, utilizing Bi-LSTM and CRF, integration of the Focal Loss function to tackle sample imbalance and a reinforcement learning-based noise reduction method for handling dataset noise. Experiments on relation extraction datasets indicate the superiority of the CasRelBLCF model and the enhancement on model's performance of the noise reduction method.

Antibiotic resistance genes and mobile genetic elements in different rivers: The link with antibiotics, microbial communities, and human activities.

Rivers as a critical sink for antibiotic resistance genes (ARGs), and the distribution and spread of ARGs are related to environmental factors, human activities, and biotic factors (e.g. mobile genetic elements (MGEs)). However, the potential link among ARGs, microbial community, and MGEs in rivers under different antibiotic concentration and human activities remains unclear. In this study, 2 urban rivers (URs), 1 rural-urban river (RUR), and 2 rural rivers (RRs) were investigated to identify the spatial-temporal variation and driving force of ARGs. The total concentration of quinolones (QNs) was 160.1-2151 ng·g-1 in URs, 23.34-1188 ng·g-1 in RUR, and 16.39-85.98 ng·g-1 in RRs. Total population (TP), gross domestic production (GDP), sewage, industrial enterprise (IE), and IEGDP appeared significantly spatial difference in URs, RUR, and RRs. In terms of ARGs, 145-161 subtypes were detected in URs, 59-61 subtypes in RURs, and 46-79 subtypes in RRs. For MGEs, 55-60 MGEs subtypes were detected in URs, 29-30 subtypes in RUR, and 29-35 subtypes in RRs. Significantly positive correlation between MGEs and ARGs were found in these rivers. More ARGs subtypes were related to MGEs in URs than those in RUR and RRs. Overall, MGEs and QNs showed significantly direct positive impact on the abundance of ARGs in all rivers, while microbial community was significantly positive impact on the ARGs abundance in URs and RUR. The ARGs abundance in URs/RUR were directly positive influenced by microbial community/MGEs/socioeconomic elements (SEs)/QNs, while those in RRs were directly positive influenced by QNs/MGEs and indirectly positive impacted by SEs. Most QNs resistance risk showed significantly positive correlation with the abundance of ARGs types. Therefore, not only need to consider the concentration of antibiotics, but also should pay more attention to SEs and MGEs in antibiotics risk management and control.

An evaluation of cervical maturity for Chinese women with labor induction by machine learning and ultrasound images.

BACKGROUND: To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. METHODS: The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. RESULTS: The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost (p = 0.0017). The p-value of the other two models was < 0.01. CONCLUSION: In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method.

A deep supervised transformer U-shaped full-resolution residual network for the segmentation of breast ultrasound image.

PURPOSE: Breast ultrasound (BUS) is an important breast imaging tool. Automatic BUS image segmentation can measure the breast tumor size objectively and reduce doctors' workload. In this article, we proposed a deep supervised transformer U-shaped full-resolution residual network (DSTransUFRRN) to segment BUS images. METHODS: In the proposed method, a full-resolution residual stream and a deep supervision mechanism were introduced into TransU-Net. The residual stream can keep full resolution features from different levels and enhance features fusion. Then, the deep supervision can suppress gradient dispersion. Moreover, the transformer module can suppress irrelevant features and improve feature extraction process. Two datasets (dataset A and B) were used for training and evaluation. The dataset A included 980 BUS image samples and the dataset B had 163 BUS image samples. RESULTS: Cross-validation was conducted. For the dataset A, the proposed DSTransUFRRN achieved significantly higher Dice (91.04 ± 0.86%) than all compared methods (p < 0.05). For the dataset B, the Dice was lower than that for the dataset A due to the small number of samples, but the Dice of DSTransUFRRN (88.15% ± 2.11%) was significantly higher than that of other compared methods (p < 0.05). CONCLUSIONS: In this study, we proposed DSTransUFRRN for BUS image segmentation. The proposed methods achieved significantly higher accuracy than the compared previous methods.

Step-feeding food waste fermentation liquid as supplementary carbon source for low C/N municipal wastewater treatment: Bench scale performance and response of microbial community.

Municipal wastewater treatment often lacks carbon source, while carbon-rich organics in food waste are deficiently utilized. In this study, the food waste fermentation liquid (FWFL) was step-fed into a bench-scale step-feed three-stage anoxic/aerobic system (SFTS-A/O), to investigate its performance in nutrients removal and the response of microbial community as a supplementary carbon source. The results showed that the total nitrogen (TN) removal rate increased by 21.8-109.3% after step-feeding FWFL. However, the biomass of the SFTS-A/O system was increased by 14.6% and 11.9% in the two phases of the experiment, respectively. Proteobacteria was found to be the dominant functional phyla induced by FWFL, and the increase of its abundance attributed to the enrichment of denitrifying bacteria and carbohydrate-metabolizing bacteria was responsible for the biomass increase. Azospira belonged to Proteobacteria phylum was the dominant denitrifying genera when step-fed with FWFL, its abundance was increased from 2.7% in series 1 (S1) to 18.6% in series 2 (S2) and became the keystone species in the microbial networks. Metagenomics analysis revealed that step-feeding FWFL enhanced the abundance of denitrification and carbohydrates-metabolism genes, which were encode mainly by Proteobacteria. This study constitutes a key step towards the application of FWFL as a supplementary carbon source for low C/N municipal wastewater treatment.

Deep-Learning-Based Ultrasound Sound-Speed Tomography Reconstruction with Tikhonov Pseudo-Inverse Priori.

Ultrasound sound-speed tomography (USST) is a promising technology for breast imaging and breast cancer detection. Its reconstruction is a complex non-linear mapping from the projection data to the sound-speed image (SSI). The traditional reconstruction methods include mainly the ray-based methods and the waveform-based methods. The ray-based methods with linear approximation have low computational cost but low reconstruction quality; the full wave-based methods with the complex non-linear model have high quality but high cost. To achieve both high quality and low cost, we introduced traditional linear approximation as prior knowledge into a deep neural network and treated the complex non-linear mapping of USST reconstruction as a combination of linear mapping and non-linear mapping. In the proposed method, the linear mapping was seamlessly implemented with a fully connected layer and initialized using the Tikhonov pseudo-inverse matrix. The non-linear mapping was implemented using a U-shape Net (U-Net). Furthermore, we proposed the Tikhonov U-shape net (TU-Net), in which the linear mapping was done before the non-linear mapping, and the U-shape Tikhonov net (UT-Net), in which the non-linear mapping was done before the linear mapping. Moreover, we conducted simulations and experiments for evaluation. In the numerical simulation, the root-mean-squared error was 6.49 and 4.29 m/s for the UT-Net and TU-Net, the peak signal-to-noise ratio was 49.01 and 52.90 dB, the structural similarity was 0.9436 and 0.9761 and the reconstruction time was 10.8 and 11.3 ms, respectively. In this study, the SSIs obtained with the proposed methods exhibited high sound-speed accuracy. Both the UT-Net and the TU-Net achieved high quality and low computational cost.

A VGG attention vision transformer network for benign and malignant classification of breast ultrasound images.

PURPOSE: Breast cancer is the most commonly occurring cancer worldwide. The ultrasound reflectivity imaging technique can be used to obtain breast ultrasound (BUS) images, which can be used to classify benign and malignant tumors. However, the classification is subjective and dependent on the experience and skill of operators and doctors. The automatic classification method can assist doctors and improve the objectivity, but current convolution neural network (CNN) is not good at learning global features and vision transformer (ViT) is not good at extraction local features. In this study, we proposed a visual geometry group attention ViT (VGGA-ViT) network to overcome their disadvantages. METHODS: In the proposed method, we used a CNN module to extract the local features and employed a ViT module to learn the global relationship among different regions and enhance the relevant local features. The CNN module was named the VGGA module. It was composed of a VGG backbone, a feature extraction fully connected layer, and a squeeze-and-excitation block. Both the VGG backbone and the ViT module were pretrained on the ImageNet dataset and retrained using BUS samples in this study. Two BUS datasets were employed for validation. RESULTS: Cross-validation was conducted on two BUS datasets. For the Dataset A, the proposed VGGA-ViT network achieved high accuracy (88.71 ± $\ \pm \ $ 1.55%), recall (90.73 ± $\ \pm \ $ 1.57%), specificity (85.58 ± $\ \pm \ $ 3.35%), precision (90.77 ± $\ \pm \ $ 1.98%), F1 score (90.73 ± $\ \pm \ $ 1.24%), and Matthews correlation coefficient (MCC) (76.34 ± 7 $\ \pm \ 7$ 3.29%), which were better than those of all compared previous networks in this study. The Dataset B was used as a separate test set, the test results showed that the VGGA-ViT had highest accuracy (81.72 ± $\ \pm \ $ 2.99%), recall (64.45 ± $\ \pm \ $ 2.96%), specificity (90.28 ± $\ \pm \ $ 3.51%), precision (77.08 ± $\ \pm \ $ 7.21%), F1 score (70.11 ± $\ \pm \ $ 4.25%), and MCC (57.64 ± $\ \pm \ $ 6.88%). CONCLUSIONS: In this study, we proposed the VGGA-ViT for the BUS classification, which was good at learning both local and global features. The proposed network achieved higher accuracy than the compared previous methods.

Metal(loid) flux change in Dongting Lake due to the operation of Three Gorges Dam, China.

A drastic decrease in the suspended sediment of Dongting Lake (DTL) has been observed due to Three Gorges Dam (TGD) impoundment operation since 2003. However, the relationship between sediment loads and metal fluxes has not been studied. This study comprehensively analyzed the content characteristics of seven metal(loid)s (As, Cd, Cr, Cu, Hg, Pb, and Zn) in the surface sediment of DTL from 2000 to 2019. The period of 2005-2009 corresponded to a metal(loid) enrichment stage in the sediment of DTL. The metal(loid) cumulative input of DTL from 2000 to 2019 reached 153 × 103 t, and the increasing rate was gradually diminished because of TGD operation, while the metal(loid) cumulative output reached 132 × 103 t. Undergoing an input-output state transition, the metal(loid) cumulative deposition of DTL in 2019 was only 42% of its peak in 2007. Especially, the metal(loid) fluxes of DTL all became negative for the first time in 2006. It is worth noting that Cd in DTL has shifted to a net export during the study period. Finally, the assessment results of pollution, risk, and toxicity indicated that metal(loid) effects on sediment quality were weakening in recent years. This study confirmed that DTL has shifted from metal(loid) deposition to export, providing new information for future DTL management options.

Twenty years of China's water pollution control: Experiences and challenges.

Water pollution is a major environmental problem worldwide, especially in developing countries. China's environmental protection strategies have been pushed to the highest priority in history, driving remarkable achievements in water pollution control, but were also coupled with new challenges. In this study, we analyzed diverse long-term data (i.e. water quality, WWTPs, pollutant discharge etc.) to systematically understand the process of water pollution control in China in the last twenty years. The results highlighted that the collection and treatment capacity of wastewater in China approached the developed country level, with the treatment rates exceeding 90% both in urban and country areas. The environmental quality of surface water was continuously improved, but water pollution problems remained in the river basins of eastern China, with remarkable economic progress. Rapid economic growth rather than population growth was the limiting factor for water pollution control in China. Therefore, more efforts should be made to further improve wastewater collection and treatment capacity and address the gap between effluent discharge limits for wastewater treatment plants and environmental quality standards for surface water. China's progress toward water pollution control provided important insights for other developing countries.

Constructed wetland substrates: A review on development, function mechanisms, and application in contaminants removal.

Constructed wetlands (CWs) are economical, efficient, and sustainable wastewater treatment method. Substrates in CWs inextricably link with the other key components and significantly influence the performance and sustainability of CWs. Gradually, CWs have been applied to treat more complex contaminants from different fields, thus has brought forward new demand on substrates for enhancing the performance and sustainability of CWs. Various materials have been used as substrates in CWs, and their individual characteristics and application advantages have been extensively studied in recent years. Therefore, this review summarizes the development, function mechanisms (e.g., filtration, adsorption, electron supply, supporting plant growth and microbial reproduction), categories, and applications of substrates in CWs. The interaction mechanisms of substrates with contaminants/plants/microorganisms are comprehensively described, and the characteristics and advantages of different substrate categories (e.g., Natural mineral materials, chemical products, biomass materials, industrial and municipal by-products, modified functional materials, and novel materials) are critically evaluated. Meanwhile, the influences of substrate layer arrangement and synergism on contaminants removal are firstly systematically reviewed. Furthermore, further research about substrates (e.g., clogging, life cycle assessment/management, internal relationship between components) should be systematically carried out for improving efficiency and sustainability of CWs.

Assessment methodology applied to arsenic pollution in lake sediments combining static and dynamic processes.

The fraction transformation from stable to mobile forms in sediments is continuous, slow, and spontaneous chain reactions causing static risks to the aquatic system. However, this process may change into abrupt, rapid, and dynamic paths when certain physicochemical conditions changed. Using the Delayed Geochemical Hazard (DGH) model, comprehensive methods combing both static and dynamic risk assessment were therefore conducted to evaluate the aforementioned processes. By applying these methods, arsenic (As) pollution in surface sediments of the Baiyangdian Lake (BYD Lake) was investigated thoroughly as a case study area. The results showed that the total As concentrations in those sediment samples ranged from 4.87 to 17.94 mg/kg, with an average of 8.75 mg/kg. In a fraction, Fe and Mn were observed to pose effects on the surface-adsorbed (AsS) and residual fractions (AsR) with the coefficient analysis. The static risk assessment showed that both the contamination and ecological risk are at a low level in the total content but a low to moderate risk in the fraction. The dynamic risk assessment posted the potential transformation paths of As in the sediments, indicating a trend of potential DGH burst in 45.24%-78.57% of the BYD Lake. In summary, this study provides a methodology for the risk assessment of arsenic that may extend to other heavy metal(loid)s combining static and dynamic processes in sediments.

A review on China's constructed wetlands in recent three decades: Application and practice.

Constructed wetlands (CWs) have been introduced to and developed in China for environmental engineering over the most prosperous three decades (1990-2020). To study the origin, development process, and future trend of CWs, this review summarized a wide range of literatures between 1990 and 2020 by Chinese authors. Firstly, the publication number over years, research highlights, and the author contributions with the most published papers in this field were conducted through bibliometric analysis. Secondly, the most principal components of CWs, substrates and macrophytes were summarized and analyzed. Thirdly, the typical application cases from traditional CWs, pond systems to combined pond-wetland systems were presented. In China, CWs were predominately distributed in the east of the so-called 'Hu Huanyong Line'. Therefore CWs were limited by the socio-economic level and climatic conditions. It is unquestionable that the overall level of China's CWs has improved significantly, and one of the most prominent features has started towards the plural pattern development. There has been a trend of large-scale or low-cost CW application in the recent years. However, lifecycle research and management are required for better strategies in the future.

New insights into restoring microbial communities by side-stream supersaturated oxygenation to improve the resilience of rivers affected by combined sewer overflows.

Combined sewer overflows (CSOs) are a dominant contributor to urban river pollution. Therefore, reducing the environmental impacts of CSOs and improving the self-purification capacity of water bodies are essential. In this study, the side-stream supersaturation (SSS) oxygenation was applied to restore microbial function of rivers which are affected by CSOs to improve the self-purification capacity. The results showed that apart from the dissolved organic matter inputs from CSO event, the sediment had become an important contributor to pollution in the studied river. After the long-term (46 d) implementation of SSS oxygenation, dissolved oxygen and the oxidation-reduction potential of the river water increased by 98% and 238%, respectively, compared to emergency control measures implemented following individual CSO events. The NH3-N concentrations and the chemical oxygen demand also decreased by 20% and 45%, respectively. In addition, the occurrence of microbial functions related to information storage and processing, and cellular process and signaling, increased by 1.87% and 0.82% in response to SSS oxygenation, respectively, and the Shannon index of the sediment microbial community increased by more than 15%. The frequencies of genes related to nitrification and sulfur oxidation also increased by 20-450% and >50%, respectively. This research provides new insights into the ecological restoration of rivers affected by CSOs.

Osseous Rosai-Dorfman disease of tibia in children: A case report.

BACKGROUND: Rosai-Dorfman disease (RDD), or sinus histiocytosis with massive lymphadenopathy, is a benign histiocytic disorder. Extranodal involvement is common, occurring in > 40% of patients, but bone involvement occurs in < 10% of cases. In addition, primary bone RDD is extremely rare. The majority of patients are adolescents and young adults, and the mean age at onset is 20-years-old. CASE SUMMARY: We report an 8-year-old Chinese girl who presented to our hospital with an insidious onset of swelling and pain in the middle shaft of her right tibia for 4 mo. We performed total surgical resection of the right tibia lesion and allograft transplantation. A good prognosis was confirmed at the 6 mo follow-up. Pain and swelling symptoms were totally relieved, range of motion of her right knee and ankle returned to normal, and there was no clinical evidence of lesion recurrence at last follow up. Our case is the second reported case of osseous RDD without lymphadenopathy in the shaft of the tibia of a child. CONCLUSION: Extranodal RDD is a rare disease and can be misdiagnosed easily. Lesion resection and allograft transplantation are an option to treat extranodal RDD in children with good short term result. Pediatric orthopedist should be aware of this rare disease, especially extranodal involvement.

Spatial and temporal distribution of Mo in the overlying water of a reservoir downstream from mining area.

This study aimed to evaluate the spatial and temporal variations of molybdenum (Mo) in the downstream water body of a Mo mine during three hydrologic periods (wet, dry and medium seasons). The physical properties in Luhun Reservoir reflected seasonal variations in different hydrological periods. The redox potential (ORP) and dissolved oxygen (DO) increased in the dry season. The concomitant decrease in temperature (T), conductivity (COND) and total dissolved solids (TDS) were lowest in the wet season. The pH value did not change significantly during the three hydrologic periods. The distribution of Mo in the dry season was high in upstream and low in downstream areas, which was significantly different from that of the wet and medium seasons. The total Mo concentration in wet (150.1 µg/L) and medium season (148.2 µg/L) was higher than that in the dry season, but the TDS (288.3 mg/L) and the percentage dissolved Mo (81.3%) in overlying water was lowest in the wet season. There was no significant relationship between the dissolved Mo and the total Mo with TDS. In the dry season, the mean total Mo concentration was 116.3 µg/L, which was higher than the standard limit value (70 µg/L) for drinking water (US EPA-United States Environmental Protection Agency recommended value 40 µg/L). Non-point source pollution is the main characteristic of mining area pollution, which was closely related to rainfall. Thus, the Luhun Reservoir contains substantial Mo pollution, which was a significant concern given that it is used as a source of drinking and irrigation water.

Net anthropogenic nitrogen and phosphorus inputs in Pearl River Delta region (2008-2016).

Excess inputs of nitrogen (N) and phosphorus (P) are the main contributors of aquatic environmental deterioration. Due to the agricultural and industrial activities in the rapidly urbanized basin, the anthropogenic N and P cycle are significantly different from other regions. In this study, we took the Pearl River Delta as an example and introduced the budget list of N and P in the five survey years, including the net anthropogenic N inputs (NANI) and net anthropogenic P inputs (NAPI). The results revealed that the intensities of NANI and NAPI in this area increased from 2008 to 2010 and then decreased after 2010. The peak values were 21001 kg N km-2yr-1 and 4515 kg P km-2yr-1 for the intensities of NNAI and NAPI, respectively, while the lowest values decreased to 19186 kg N km-2yr-1 and 4103 kg P km-2yr-1 in 2016. The most important contribution of NANI and NAPI sources in this area were net N and P inputs for human food and animal feed with an average contribution of 61.41% and 76.83%, which indicated that large amounts of N and P were introduced into the environment through the food system. This study expanded the knowledge on regional environmental management from human dietary consumption, human life consumption, animal consumption and fertilizer consumption. Its reuse will be put into practice by understanding the driving factors of N and P inputs in each region of the basin, combining the urbanization characteristics.

Molybdenum contamination dispersion from mining site to a reservoir.

This study was conducted to assess heavy metals in the overlying water and sediments of Luhun Reservoir, Henan Province, China, which is positioned downstream from a molybdenum (Mo) mining area. The pollution indexes indicated that deposition of all metals may have been affected by the mining area. The single element pollution factor (Pi) of Mo was the highest among all heavy metals, with a mean value of 2.05. However, the sediments were subject to long-term accumulation of metals, particularly Mo, Cd, Pb, and Zn, which originated from anthropogenic sources. The mean individual element potential ecological risk index values for Cd were above 385, while the mean value comprehensive potential ecological risk index was 465, which indicates a high ecological risk. Moreover, the enriched heavy metals had different spatial distributions in the Luhun Reservoir sediments. Finally, Pearson correlation analysis indicated that the Pb was mainly affected by different anthropogenic sources and had no relationship with other metals, which suggests that the influence of mining area on heavy metal concentrations in the reservoir is difficult to disentangle.

Spatial Distributions, Sources and Risks of Polycyclic Aromatic Hydrocarbons in Sediments from Ziya River System, Northern China.

With the development of urbanization and industrialization, Ziya River Plain (ZYRP) had become one of the most polluted regions of polycyclic aromatic hydrocarbons (PAHs) in north China. The distribution of PAHs in sediments were investigated, and then their sources and risks were evaluated. The results showed that the total PAHs varied from 3372 to 92,948 µg/kg, and heavy pollution was found in the upstream. Both the isomer pair ratios of PAH and principal components analysis (PCA) revealed that fossil fuel combustion was the mainly contributes (69.1%), followed by wood and coal combustion (26.7%). The ecological risk for the whole area was moderate, with the highest risk in Niuwei River (NWR). and significant correlation was found between the ecological risk and high-molecular-weight (HMW) of PAHs (r2 > 0.99, p < 0.01). Our findings would give insights into the mitigation of sedimentary PAHs pollution in north China.