The Filter Inlet for Gases and AEROsols coupled to a Chemical Ionization Mass Spectrometer (FIGAERO-CIMS) can be used to derive volatility of atmospheric aerosol by using the temperature at thermogram maximum signal (Tmax). For complex ambient particle matrices, Tmax of an individual compound often varies, for reasons not fully elucidated. Here, we apply machine learning to study the relation between Tmax of levoglucosan (C6H10O5), a common tracer to identify the influence of biomass burning (BB) in ambient air, and a set of atmospheric and instrumental parameters for an ambient year-long FIGAERO-CIMS data set measured in the Arctic. Using three different modeling approaches, namely, multiple linear regression (MLR), random forest (RF) regressor, and XGBoost regressor, we find that the mass loading on the FIGAERO filter has the highest relevance for variation in Tmax of levoglucosan. On the basis of these results, we suggest controlling the mass collected on the filter for continuous online measurement with the FIGAERO-CIMS if quantitative volatility information is to be gained. More generally, we demonstrate the usefulness of machine learning approaches for characterization of instrumental backgrounds in complex ambient or laboratory data.

Ethylene glycol (EG) serves as the primary hydrolysis product of polyethylene terephthalate (PET), making its electro-oxidation reaction (EGOR) a key pathway for high-value plastic waste utilization. However, conventional coupled strategy fails to meet the dual requirements of EG dehydrogenation and hydroxyl species (*OH) supply. This functional incompatibility hinders catalytic performance by limited intermediate conversion, inducing site poisoning and reducing GA selectivity. We design a site-decoupled strategy to address these problems, where Pt sites drive EG dehydrogenation while oxophilic Co oxyhydroxides facilitate hydroxylation via *OH supply. Crucial to this design is the Co-O-Pt bridging-oxygen structure, which establishes a rapid electronic coupling channel, optimizes intermediate adsorption, and accelerates charge transfer. The PtCo-Ni(OH)2@NF exhibits a mass activity of 9.87 A mg Pt-1 with 92.8% Faradaic efficiency and 97.3% selectivity toward GA, achieving a 6.8-fold enhancement in cumulative GA production over the coupled strategy. The system sustains operation for 300 h with negligible decay. Scalability tests using 100.0 g of real-world PET yielded 81.1 g PTA (93.8% yield) and 23.1 g GA (58.4% yield). Techno-economic analysis estimates a potential profit of ∼US$515.5 per ton of waste PET, demonstrating this strategy as a promising pathway for high-value upcycling of diverse polyester and polyol feedstocks.

Environmental exposure to toxic chemicals has long been suspected an important factor contributing to autism spectrum disorder (ASD) in children. Our study developed a suspect screening strategy to broaden the understanding of neurotoxicant exposure in children with ASD (n = 307) and healthy controls (n = 461) and the association between ASD and mixed chemical exposure. Suspect screening of urine samples from the study population identified a total of 94 neurotoxicants designated as confidence level 1, with additional 16 and 34 compounds designated as confidence level 2 and 3, respectively. Among identified level 1 compounds, 48 had a detection frequency >70% in the study population, covering plasticizers, polycyclic aromatic hydrocarbons, insecticides, flame retardants, ultraviolet filters, antimicrobial agents and synthetic antioxidants. The results reveal a complexity of exposure spectrum in ASD children. Conditional logistic regression analyses with level 1 compounds revealed significant associations between ASD and increasing urinary levels of 28 neurotoxicants. Mixed exposure analysis revealed a strong association between combined neurotoxicant exposure and the ASD diagnosis. Among the diversity of neurotoxicants, 1,3-diphenylguanidine (DPG), diphenyl phosphate (DPP) and mono (2-ethyl-5-carboxypentyl) phthalate (mECPP) were identified as the key substances contributing to the exposure-ASD associations. Collectively, our work reported a complex neurotoxicant exposure spectrum in ASD children and associations between neurotoxicant exposure and ASD. The findings highlight the complexity of neurotoxicant exposure in children and the importance of exploring environmental factors of ASD.

Several approaches have been used to reproduce the environmental aging of microplastics (MPs) in the laboratory; however, because they are based on different oxidizing species, they may lead to MPs with distinct surface properties and environmental behavior. This study compares the impact of ultraviolet (UV), ozone, and activated persulfate aging on the surface chemistry and contaminant adsorption of high-density polyethylene MPs aged to identical carbonyl index (CI) values. Surface characterization of aged MPs revealed crucial structural differences between the aging protocols: at the same CI of 0.1, the surface-oxidized carbon content was higher for persulfate-aged MPs (2.74%) than for UV (2.18%) or ozone (2.23%). Persulfate aging also resulted in higher specific surface area, going from 0.22 m2/g (pristine MPs) to 0.79 m2/g at a CI of 0.1, compared with 0.67 and 0.56 m2/g for ozone and UV aging. Isotherm experiments with phenanthrene showed a decrease in adsorption with surface oxidation, while, for 9-phenanthrol, adsorption was higher for UV- and ozone-aged MPs than pristine MPs and declined for the highly oxidized persulfate-aged MPs. These results demonstrate that different oxidation strategies produce structurally and functionally distinct MPs, highlighting the importance of the aging protocol in laboratory studies.

6PPDQ, an emerging environmental pollutant derived from tire wear, has gained widespread attention due to its high acute toxicity toward salmonids, such as rainbow trout. It has been found to induce neurotoxic effects at environmentally relevant concentrations; yet, the underlying mechanisms remain elusive. Moreover, methods for the specific identification of 6PPDQ-interacting proteins are still lacking. Herein, we developed a clickable probe (6PPDQ-yne) and confirmed that it induces neurotoxic effects in rainbow trout similar to those caused by 6PPDQ through an acute lethality assay, neurobehavioral experiments, and histopathological analysis. We then employed the clickable probe to perform unbiased compound-centric chemical proteomics (CCCP) and systematically deconvoluted 6PPDQ target proteins in rainbow trout brains. The CCCP analysis identified 2,502 high-confidence target proteins, of which GS was selected for further investigation. Our results demonstrated that 6PPDQ directly binds to GS and downregulates its enzymatic activity. In fish brains, the inhibition of GS activity by 6PPDQ disrupted the glutamate-glutamine cycle and caused glutamate accumulation, which induced a massive calcium ion influx and ultimately triggered cell death. In summary, our study validates a critical protein target, laying a foundation for elucidating 6PPDQ-induced neurotoxicity mechanisms and providing a systematic paradigm for deconvoluting the toxicity mechanisms of emerging pollutants.

Habitat fragmentation may amplify antibiotic resistance genes (ARGs), yet the ecological pathways linking landscape patterns to host resistomes in intertidal systems remain unclear. Macrobenthic organisms as potential reservoirs and dispersal nodes are ideal models. Focusing on the horseshoe crab (Tachypleus tridentatus), a food web hub and habitat indicator, we integrated landscape metrics, metagenomics, and path modeling (PLS-PM) to examine, across fragmented habitats, links among sediment physicochemistry, larval diet, gut microbiota, mobile genetic elements (MGEs), and ARGs. Results revealed that more fragmented habitats promoted individuals with higher ARG abundance and diversity, alongside stronger MGE enrichment and increased ARG-MGE co-occurrence, indicating enhanced mobility potential. Fragmentation also coincided with greater dietary diversity but higher among-individual convergence, selective assembly of gut microbiota with higher diversity, and tight ARG-MGE association. PLS-PM supported a diet-gut microbiota-MGE-ARG cascade, while the direct effects of sediment chemistry were not significant. Attributing ARG hosts at the MAG level, Enterobacteriaceae and Vibrionaceae dominated ARG abundance and enrichment, indicating lineage selectivity. Multidrug and polymyxin resistance was most prominent. These findings identify key AMR risk pathways and inform priority interventions for T. tridentatus and habitat conservation. The developed assessment framework is scalable and offers a paradigm for One Health management in mudflat systems.

BTX (benzene, toluene, and xylene), as representative indoor volatile organic compounds (VOCs), poses persistent threats to human health. However, achieving the efficient catalytic degradation of BTX at low temperatures remains a major challenge. In this study, a multilevel three-dimensional (3D) MnOx/Cu-MOF/CNTs conductive aerogel catalyst was constructed, and an electroinjection (EI)-assisted catalytic oxidation strategy was proposed for BTX degradation. When the EI power was set to 1 W, the removal efficiency and yield of o-xylene reached 99.61% and 82.56%, respectively. Density functional theory (DFT) calculations further demonstrate that the EI strategy can modulate the charge density around Mn and reduce oxygen vacancy formation energy. Overall, this work provides a new paradigm for overcoming the bottleneck of the low-temperature catalytic degradation of VOCs.

Reducing methane emissions can slow near-term warming, yet building accurate inventories to inform mitigation efforts and track progress toward reduction targets remains challenging. We present a 2024 source-resolved methane inventory for the Permian Basin, built from quarterly aerial LiDAR scans. We combined public infrastructure records with machine learning identification of non-producing sites to define the facility population and generate sampling plans and then deployed Bridger Photonics' Gas Mapping LiDAR to scan 51,785 sites across four quarters. Sources were localized within 2 m and attributed to equipment acquired by aerial photography during scans. We detail a Monte Carlo framework that propagates quantification, extrapolation, sampling, and detection sensitivity uncertainty and weights spatial extrapolation by observed equipment counts, avoiding bias from over- or under-sampling of large facilities. The workflow yields a source-resolved inventory down to 0.4 kg/h with quarterly temporal resolution. Total annual basin emissions were 5,133 kt CH4 after adding gathering pipelines and subthreshold emissions from prior studies. Emissions were seasonal, with the winter up to 17% higher than the summer. The basin-wide methane loss rate was 3.13%. Texas emitted 4,038 kt CH4 with a 3.6% loss rate, while New Mexico emitted 1,095 kt CH4 with a 2.1% loss rate. At the operator level, most large operators outperformed the basin average intensity by a wide margin.