The inhibitory effect of hydrophilic volatile organic compounds (VOCs) on hydrophobic VOCs removal was found to be efficiently reduced by the fungal-bacterial biofilters (F&B-BFs) developed in the present study. Overall, the toluene and ethyl acetate mixture removal efficiencies (REs) and elimination capacities (ECs) of F&B-BFs were superior to those of bacterial biofilters (B-BFs). The REs for toluene and ethyl acetate were 32.5 ± 0.8 % and 74.6 ± 1.0 %, respectively, for F&B-BFs, in comparison to 8.0 ± 0.3 % and 60 ± 1.3 % for B-BFs. The ECs for toluene and ethyl acetate were 13.0 g m⁻³ h⁻¹ and 149.2 g m⁻³ h⁻¹, respectively, for the F&B–BF, compared to 3.2 g m⁻³ h⁻¹ and 119.6 g m⁻³ h⁻¹ for the B-BFs. This was achieved at a constant empty bed residence time (EBRT) of 45 s. F&B-BFs exhibited a superior mineralization efficiencies (MEs) compared to B-BFs for a VOC mixture of toluene and ethyl acetate (≈36.1 % vs ~ 29.6 %). This is attributed to the direct capture of VOCs by the presence of fungi, increased the contact time between VOCs and VOCs-degrading bacteria, and even distribution of VOCs-degrading bacteria in the F&B-BFs. Moreover, compared with B-BFs, the coupling effect of genus Pseudomonas degradation, and unclassified_f_Herpotrichiellaceae and unclassified_p_Ascomycota adsorption of F&B–BF resulted in a reduction in the impact of the presence of hydrophilic VOCs on the removal of hydrophobic VOCs, thereby enhancing the biofiltration performance of mixtures of hydrophilic and hydrophobic VOCs.

Faced with the intertwined challenges of climate change, pollution dispersion, ecosystem degradation, and resource constraints, the global environment exhibits high nonlinearity, multiscale coupling, and regional variability (Zhu et, al., 2023).Traditional experimental methods and statistical tools are often constrained by high costs, reliance on complex instrumentation, and an inability to capture intrinsic dynamics or provide interpretable decision support across large spatiotemporal scales.In recent years, computational modeling integrated with modern techniques, such as artificial intelligence, machine learning, molecular simulation, and computational fluid dynamics, has offered new ways to address environmental complexities (Jeong and Choi, 2022;Liu et, al., 2022). These tools help assess toxicity and risks, identify pollution sources, and elucidate pollutant behavior across media. Despite significant progress, most current applications rely on off-the-shelf algorithms, while reusable models designed specifically for environmental problems remain scarce (Alotaibi and Nassif, 2024). This limits the discovery of underlying mechanisms and hinders the practical application of models in environmental management and pollution control. Moreover, the "black-box" nature of environmental input-output relationships makes model interpretation difficult (Zhu et, al., 2023;Xu et, al., 2024). Hence, this special issue focuses on three core questions: how to improve the cost-effectiveness and practical applicability of environmental solutions via computational modeling; how to integrate data-driven approaches with domain knowledge for mechanistic interpretation of environmental processes; and how to develop practical frameworks that handle missing data and spatial heterogeneity.This Research Topic features ten articles, including both original research and reviews, on computational modeling applied to pollutant source apportionment, environmental behavior, toxicity, risk, and removal. All of them address diverse environmental problems with a problem-driven modeling approach and provide practical technical solutions. Third, traditional source apportionment methods have long been limited to qualitative or semi-quantitative estimates of source contributions, making it difficult to directly link them to ecological or health risks. Two studies improved the methodology at regional and site scales. Zhai conducted a meta-analysis of volatile organic compounds (VOC) emissions and ozone formation potential (OFP) across 14 cities in the Pearl River Delta, Yangtze River Delta, and Bohai Rim. The study revealed that oxygenated VOCs dominate emissions (44.6%-81.1%), with isopropanol and ethyl acetate as main compounds; OFP ranged from 78.5 to 644 mg/m 3 , highest in Changsha. About 68% of enterprises use inefficient technologies (e.g., granular activated carbon), while efficient regenerative thermal oxidizers are not widely adopted due to cost and policy constraints. This work provides a scientific basis for region-specific VOC reduction and ozone control. Liang et al. focused on a decommissioned coking site, building a quantitative source-risk framework with GIS, positive matrix factorization (PMF), and Monte Carlo simulation. Results showed that ecological risks were mainly from coking industry Hg emissions, while health risks were driven by Cd and As from agricultural activities. The framework demonstrated that "high mass contributions do not equal high risks", offering guidance for environmental management and safe urban renewal.Finally, environmental monitoring and forecasting rely on data completeness, regional representativeness, and the ability to capture complex dynamics. Four studies addressed missing data interpolation, forecasting under regional heterogeneity, and In summary, the articles collected under this research topic highlight and elucidate the role of computational modeling in developing low-cost detection methods, energy-saving remediation strategies, quantitative source-risk frameworks, and reliable forecasting tools for environmental monitoring. This research topic has positive implications for deepening the understanding of complex environmental processes and for developing practical, mechanism-driven modeling solutions that support environmental management and pollution control.