This study investigated soil and groundwater contamination at an in-service oil transportation station in the middle-lower Yellow River Basin, China. Spatial analysis combined with 16S rRNA and ITS sequencing revealed localized heavy metal (Cu, Ni, Cd, Pb) and petroleum hydrocarbon (PHs: 15.0 mg/kg) contamination in the oily sewage treatment area, with vertical migration constrained by silty sand layers. Volatile organic compounds (VOCs) primarily originated from oil tank emissions. Groundwater exhibited hydraulic gradient-driven downstream migration of PHs (0.03–0.04 mg/L) and arsenic (1.1–1.5 μg/L). Indigenous microbial communities exhibited redox-stratified functional differentiation: unclassified Comamonadaceae (Proteobacteria) dominated aerobic zones (monitoring well D5), utilizing nitrate for PHs degradation, while Desulfosporosinus (Firmicutes) mediated sulfate-coupled anaerobic alkane degradation and metal immobilization in anoxic zones (D6). Fungal communities featured Trametes (Basidiomycota), facilitating ligninolytic PAH breakdown via peroxidase secretion. Functional prediction (FAPROTAX/FUNGuild) confirmed a synergistic “fungal preprocessing-bacterial mineralization” mechanism. Microbial metabolic plasticity (e.g., nitrogen respiration, photoautotrophy) enabled adaptation to redox fluctuations. Given the site’s medium-low risk profile, we proposed a tiered management framework: (1) in situ bioremediation that prioritizes indigenous microbes, (2) hierarchical risk zoning, and (3) dynamic monitoring networks. These strategies align with China’s Green Low-Carbon Remediation principles through low-energy microbial technologies. The findings provide a mechanistic basis for balancing industrial operations and ecological health in the Yellow River Basin.

PH neutralization reaction process plays a crucial role in Waste Water Treatment Process (WWTP). Traditional PID Proportion Integral Differential, (or even advanced PID control) algorithms have poor performance on WWTP due to the strong non-linearity, large time lag, and large inertia characteristics of pH neutralization. Therefore, finding a superior control method to maintain the pH value of wastewater within the normal range will greatly help to improve the efficiency and effectiveness of wastewater treatment. The chemical reaction mechanism of pH neutralization reaction process is first analyzed, and a mechanistic model of pH neutralization reaction process is developed based on the reaction of ions during acid-alkali neutralization and the electric balance equation. Then, combining the characteristics of generalized predictive control and Model-Free Adaptive Control (MFAC), a Model-Free Adaptive Predictive Control (MFAPC) method based on compact format dynamic linearization is introduced. An Improved Model Free Adaptive PI Predictive Control algorithm (IMFAPC) with proportional (P) and integral (I) algorithms is proposed to further improve the control performance. IMFAPC is proposed on the basis of MFAPC, combining the advantages of generalized predictive control, introducing a PI module consisting of error and error sum, and predicting the PI module, making it possible to produce more accurate constraints on the control inputs, avoiding increasing errors, and improving the control effect of delayed systems at the same time. pH neutralization process simulation experimental results show that compared with the ordinary Model-Free Adaptive Control (MFAC) and MFAPC, the IMFAPC control algorithms has the best performance in terms of accuracy, overshoot, and the robustness.

As the global third-largest stationary source of carbon emissions, petroleum refineries have attracted much attention. Many investigations and methodologies have been used for the quantification of carbon emissions of refineries at the industry or enterprise scale. The granularity of current carbon emissions data impairs the reliability of precise mitigation, so analysis and identification of influencing factors for carbon emissions at a more micro-level, such as unit level, is essential. In this paper, four typical units, including fluid catalytic cracking, Continuous Catalytic Reforming, delayed coking, and hydrogen production, were chosen as objects. A typical 5-million-ton scale Chinese petroleum refinery was selected as an investigating object. The Redundancy analysis and multiple regression analysis were utilized to explore the relationship between the process parameters and carbon emissions. Three types of influencing factors include reaction conditions, processing scale, and materials property. The most important mitigation of carbon emission, in this case, can be summarized as measures of improving energy efficiency via optimizing equipment parameters or prompting mass efficiency by upgrading the scale for material and energy flow.

Introduction: Top-down microbial enrichment is a reliable approach for understanding and designing microbiomes for crude oil remediation. Environmental variables serve as valuable determinants for selecting desired microbiomes with superior performance. However, the linkages between selection methods and the structure and function of desired microbiomes remain unclear. Methods: This study integrated substrate concentration gradients and cultivation patterns to investigate how selection pressures shape top-down enriched crude oil-degrading consortia. The resulting communities were analyzed using 16S rRNA gene sequencing, metagenomics, and co-occurrence network analysis. Key bacterial strains were isolated to validate their individual degradation capabilities. Results: The top-down process led to a significant reduction in phylogenetic diversity but a notable increase in the potential for xenobiotic degradation and metabolic. The final consortia, GT4, achieved a 55.72% degradation rate of crude oil at an initial concentration of 5 g/L within 7 days. Metagenomic analysis identified Microbacterium as dominant genus harboring key enzymes for the degradation of alkanes and aromatic compounds. Co-occurrence network analysis revealed Mesorhizobium as a keystone genus, showing positive associations with multiple diazotrophic bacteria and hydrocarbon degrading bacteria. Nine bacterial strains were isolated from the consortium. Among them, Microbacterium sp. WS3 and Cellulosimicrobium sp. WS9 exhibited high degradation efficiencies (57.85 and 58.60%, respectively). To the best of our knowledge, this study provides the first experimental evidence for crude oil degradation by Paracandidimonas and Caulobacter , with degradation rates of 51.19 and 40.90%, respectively. Discussion: These findings highlight the effectiveness of top-down enrichment strategy in generating functionally streamlined consortia and uncover novel oil-degrading microbes with potential for bioremediation applications.

Petroleum contamination poses a serious threat to soil ecosystems and microbial communities. Persulfate (PS)-based advanced oxidation has shown promising remediation potential; however, conventional nanoscale zero-valent iron (nZVI) suffers from surface passivation, aggregation, and limited stability in complex soil systems. To address these challenges, a biochar-supported sulfidated nanoscale zero-valent iron composite (S-nZVI@BC) was synthesized via liquid-phase reduction to enhance PS activation efficiency and improve remediation performance in crude oil-contaminated soil. Material characterization confirmed the successful loading of sulfidated nZVI onto biochar with good dispersion. At a biochar loading rate of 25%, S/Fe molar ratio of 1:10, and activated carbon particle size of 0.83 mm, the S-nZVI@BC/PS system achieved the best crude oil degradation effect. Moreover, a maximum degradation efficiency of 90.14% was achieved by employing PS and S-nZVI@BC dosages of 2 and 10%, respectively, at a water-soil ratio of 1:1. SO ₄ ^– ∙ and ∙OH are the primary species responsible for crude oil degradation, and the contribution of SO ₄ ^– ∙ was greater than that of ∙OH. After the reaction, significant reductions were observed in saturated hydrocarbons, aromatic hydrocarbons, resins, and asphaltenes. Meanwhile, The soil remediated by S-nZVI@BC/PS altered the microbial community structure and increased the relative abundance of petroleum degradation-related microorganisms. The germination rate of Elymus dahuricus increased markedly, approaching that of uncontaminated soil. These findings highlight the potential of the S-nZVI@BC/PS system as an efficient and sustainable strategy for the remediation of crude oil-contaminated soils.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in soils, and their inherent toxicity and persistence pose serious threats to terrestrial animals and plants. This study reports the synthesis of a biochar-supported Fe₂O₃/CoFe₂O₄ nanocomposite (Fe₂O₃/CoFe₂O₄@BC) as a peroxymonosulfate (PMS) activator for the degradation of PAHs in contaminated soil. The one-step prepared Fe₂O₃/CoFe₂O₄@BC exhibits abundant nanoporous structures, with a specific surface area of 158.34 m² g⁻¹ and average pore size of 2.84 nm. Compared with pristine biochar (BC), Fe₂O₃/CoFe₂O₄@BC shows superior catalytic performance in activating PMS for the efficient degradation of seven kinds of 3–4 ring PAHs in soil. Based on electron paramagnetic resonance (EPR) analysis, electrochemical analysis and scavenger quenching experiments, the catalytic mechanism was elucidated, revealing that ^•OH, SO₄^•−, and electron transfer were primarily responsible for the degradation of phenanthrene (PHE) in soil. The presence of coexisting soil constituents, including Cl⁻, HCO₃⁻, NO₃⁻ and humic acid (HA), was found to inhibit PHE degradation. Furthermore, plant growth experiments revealed that the Fe₂O₃/CoFe₂O₄@BC/PMS system effectively alleviated the ecotoxicity of PHE-contaminated soil. This work thus provides a promising nanocatalyst for PMS-mediated remediation of soil contaminated with refractory organic pollutants and offers a feasible strategy for the in situ chemical remediation of PAH-polluted soil.