The BP neural network model predicted the PAH soil composition of Beijing's gas stations for the years 2025 and 2030. The total concentration of the seven PAHs was observed to vary from 0.001 to 3.53 milligrams per kilogram in the results. The measured concentrations of PAHs fell short of the soil environmental quality risk control standard for contaminated development land (Trial) defined in GB 36600-2018. The toxic equivalent concentrations (TEQ) of the seven preceding polycyclic aromatic hydrocarbons (PAHs) measured at the same time were below the World Health Organization (WHO)'s 1 mg/kg-1 benchmark, indicating a reduced health risk. The prediction's results highlighted a positive link between the rapid growth of urbanization and the elevated presence of polycyclic aromatic hydrocarbons (PAHs) in the soil. The year 2030 will likely mark a continuation of the increasing trend of PAHs in Beijing gas station soil. For 2025 and 2030, the predicted PAH concentrations in the soil at Beijing gas stations were found to be between 0.0085-4.077 mg/kg and 0.0132-4.412 mg/kg, respectively. While the concentration of seven PAHs fell below the soil pollution risk screening threshold of GB 36600-2018, a concerning rise in PAH levels was observed over time.

To ascertain the contamination and associated health hazards of heavy metals present in agricultural soils near a Pb-Zn smelter in Yunnan Province, 56 surface soil samples (0-20 cm) were gathered, and subsequently analyzed for six heavy metals (Pb, Cd, Zn, As, Cu, and Hg), along with pH, to evaluate heavy metal levels, ecological risks, and probable health risks. The study's results revealed that the average levels of six heavy metals (Pb441393 mgkg-1, Cd689 mgkg-1, Zn167276 mgkg-1, As4445 mgkg-1, Cu4761 mgkg-1, and Hg021 mgkg-1) exceeded the background levels observed in the Yunnan region. Cadmium exhibited the paramount mean geo-accumulation index (Igeo) of 0.24, the maximal mean pollution index (Pi) of 3042, and the supreme average ecological risk index (Er) of 131260. This signifies cadmium as the primary enriched pollutant with the greatest ecological risk. Mobile social media Regarding exposure to six heavy metals (HMs), the mean hazard index (HI) was 0.242 for adults and 0.936 for children. Concerningly, 36.63% of children's HI measurements were above the 1.0 risk threshold. The average total cancer risks (TCR) for adults were 698E-05 and 593E-04 for children, respectively, with 8685% of children's values surpassing the 1E-04 guideline. Cd and As, according to the probabilistic health risk assessment, were identified as the primary drivers of non-carcinogenic and carcinogenic health risks. This study's findings will serve as a scientific benchmark for developing precise risk management and effective remediation strategies for soil heavy metal contamination within this geographical area.

To analyze the contamination characteristics and source attribution of heavy metals in farmland soils around the Nanchuan coal mine gangue heap in Chongqing, the Nemerow and Muller indexes were employed. The investigation of heavy metal sources and their contribution percentages in the soil leveraged the absolute principal component score-multiple linear regression receptor modeling (APCS-MLR) and the positive matrix factorization (PMF) methods. Downstream analyses indicated higher concentrations of Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn compared to upstream levels; however, only Cu, Ni, and Zn displayed a statistically substantial increase. The investigation into pollution sources revealed that mining activities, specifically the sustained accumulation of coal mine gangue, were the main contributors to copper, nickel, and zinc contamination. The APCS-MLR model yielded contribution rates of 498%, 945%, and 732% for each element. Glecirasib The PMF contribution rates, in order, were 628%, 622%, and 631%. Transportation and agricultural activities significantly influenced the levels of Cd, Hg, and As, leading to APCS-MLR contribution percentages of 498% for Cd, 945% for Hg, and 732% for As, and corresponding PMF contribution rates of 628%, 622%, and 631%, respectively. Concerning lead (Pb) and chromium (Cr), natural factors constituted the main influence, characterized by APCS-MLR contribution rates of 664% and 947%, and corresponding PMF contribution percentages of 427% and 477%, respectively. Substantial consistency was found in the conclusions drawn from the source analysis using the APCS-MLR and PMF receptor models.

Farmland soil health and sustainable agricultural development rely significantly on recognizing and addressing the sources of heavy metal contamination. A positive matrix factorization (PMF) model, focusing on source component spectra and source contribution, in conjunction with historical survey data and time-series remote sensing data, provided the foundation for this study's analysis of the modifiable areal unit problem (MAUP) regarding the spatial heterogeneity of soil heavy metal sources. The study employed geodetector (GD), optimal parameters-based geographical detector (OPGD), spatial association detector (SPADE), and interactive detector for spatial associations (IDSA) models, dissecting the driving factors and their interacting effects on this spatial variability, in both categorical and continuous contexts. Spatial heterogeneity in soil heavy metal sources at small and medium scales exhibited a dependency on the spatial scale utilized, and the 008 km2 spatial unit proved most effective for detecting such heterogeneity across the study area. The interplay between spatial correlation and the precision of discretization, when coupled with the quantile method, discretization parameters, and a 10-count interruption, can potentially reduce the impact of partitioning on continuous soil heavy metal variables during the identification of spatial heterogeneity in source origins. The spatial distribution of soil heavy metal sources was influenced by strata (PD 012-048) in categorical variables. The interaction between strata and watershed designations explained a range of 27.28% to 60.61% of the variation for each source. High-risk zones for each source were concentrated in the lower Sinian strata, upper Cretaceous strata, mining lands, and haplic acrisols. Continuous variables, specifically population (PSD 040-082), demonstrated control over the spatial variations in soil heavy metal sources, and the explanatory power of combined spatial continuous variables varied for each source from 6177% to 7846%. High-risk regions within each source were geographically defined by evapotranspiration (412-43 kgm-2), distance from the river (315-398 m), enhanced vegetation index (0796-0995), and a second distance from the river (499-605 m). Through this study's results, researchers can establish a benchmark for investigating the sources and interactions of heavy metals in arable soils, which forms a fundamental scientific basis for sustainable land management and growth in karst regions.

Advanced wastewater treatment facilities increasingly utilize ozonation as a regular step. The evaluation of the performance of various new technologies, diverse reactor designs, and advanced materials is integral to the development of improved ozonation-based wastewater treatment strategies by researchers. The choice of appropriate model pollutants to evaluate the capacity of novel technologies to remove chemical oxygen demand (COD) and total organic carbon (TOC) from practical wastewater specimens often mystifies them. The correlation between the COD/TOC removal capacities of pollutants reported in the literature and those observed in real wastewater samples is not immediately obvious. Developing a technological framework for advanced ozonation wastewater treatment demands careful consideration of model pollutant selection and evaluation procedures within the context of industrial wastewater. Ozonation under constant conditions was applied to aqueous solutions of 19 model pollutants and four secondary effluents from industrial parks, encompassing both unbuffered and bicarbonate-buffered varieties. Clustering analysis served as the primary tool for evaluating the degree of similarity in COD/TOC removal among the preceding wastewater/solutions. Remediation agent The study's findings indicated that the disparity in properties among the model pollutants surpassed that observed in the actual wastewater samples, thereby facilitating a logical choice of several model pollutants for evaluating the efficacy of advanced wastewater treatment using ozone-based technologies. For 60-minute ozonation processes predicting COD removal from secondary sedimentation tank effluent, unbuffered solutions of ketoprofen (KTP), dichlorophenoxyacetic acid (24-D), and sulfamethazine (SMT) produced prediction errors less than 9%. Substantially improved predictions, with errors below 5%, were obtained using bicarbonate-buffered solutions of phenacetin (PNT), sulfamethazine (SMT), and sucralose. Using bicarbonate-buffered solutions, the observed evolution of pH mirrored more closely the pH evolution in practical wastewater samples compared to the evolution observed when using unbuffered aqueous solutions. Similarity in COD/TOC removal results using ozone was observed in both bicarbonate-buffered solutions and actual wastewaters, even when varying ozone concentration conditions were considered. The protocol proposed in this study, evaluating treatment performance via wastewater similarity, is thus extendible to a variety of ozone concentration scenarios with some level of generality.

Currently, microplastics (MPs) and estrogens stand as prominent emerging contaminants, with MPs potentially acting as estrogen carriers in the environment, leading to combined pollution. The adsorption behavior of polyethylene (PE) microplastics concerning typical estrogens, including estrone (E1), 17β-estradiol (17β-E2), estriol (E3), diethylstilbestrol (DES), and ethinylestradiol (EE2), was investigated through batch adsorption experiments under equilibrium conditions. The adsorption was examined in both single-component and mixed-component systems. X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR) were utilized for characterizing the PE microplastics before and after the adsorption process.