Abstract Microdroplets, as tiny liquid particles, are ubiquitous in Earth’s atmosphere. They serve as dynamic microreactors that drive atmospheric processes, with profound implications for air quality, climate regulation, and atmospheric chemical cycles. Despite its importance, microdroplet-driven chemistry remains inadequately represented in global climate and air quality models. This perspective synthesizes emerging evidence on how microdroplet interface-enhanced multiphase chemistry modifies atmospheric processes including amplifying atmospheric oxidation capacity and accelerating the transformation of key reactive species. Advances in aerosol and microdroplet chemistry highlight the central role of the microdroplet interface in initiating accelerated kinetics and in enabling unprecedented chemical pathways distinct from those in macroscopic bulk solutions. We outline the current knowledge gaps and future directions for advancing the research in microdroplet chemistry from an atmospheric perspective. The concerted coordination among microdroplet chemistry and atmospheric communities across field, laboratory, and modeling has significant implications for understanding the critical role of microdroplet interface-driven chemistry in the atmosphere and climate change.
Abstract Endocrine-disrupting chemicals (EDCs) are increasingly implicated in chronic diseases, yet their biomonitoring in human studies still relies mainly on urine and serum, which capture only short-term exposure to these fast-elimination compounds. Here, we evaluated hair as a complementary and long-term biomonitoring matrix for EDC mixtures by integrating it into an LC-HRMS exposomics workflow together with paired serum and urine samples. We developed and validated a method targeting 44 endocrine disruptors from five chemical families (benzophenones, phthalates, parabens, bisphenols, and organophosphate esters), combining quantitative analysis with suspect screening and semi-quantification of phase II metabolites. Applied to samples from 20 postmenopausal women, the hair-based approach provided the broadest coverage and highest concentrations (31/44 compounds), up to about three orders of magnitude higher than in urine or serum, consistent with distinct accumulation mechanisms and temporal integration windows. In hair, EDCs were present in unconjugated form (>99%), whereas urine was dominated by conjugated metabolites and serum showed limited detection. Overall, these findings demonstrate that integrating hair into multimatrix exposomics designs substantially expands both the chemical and temporal resolution of human exposure assessment.
Abstract This study evaluates for the first time the sustainability of photocatalytic hydrogen production in China utilizing a 26-faced polyhedron SrTiO3/Rh/Co/Cr photocatalyst. Life cycle assessment and costing are used to estimate the impacts and levelized cost of hydrogen (LCOH). These are compared via multicriteria decision analysis with alternative solar-driven hydrogen technologies (water electrolysis, photoelectrochemical, and thermochemical), as well as with conventional methods (steam methane reforming and coal gasification). The outcomes are used to identify optimal regional configurations in different provinces that minimize both the impacts and production costs. Photocatalytic hydrogen substantially outperforms conventional methods, reducing most impacts by 21–93%, including climate change (67–93%). However, several impacts are significantly higher, increasing from 48% to 20 times. Economically, photocatalytic hydrogen is competitive with conventional methods (1.58–2.42 k$/t H2 vs 1.18–2.38 k$/t H2). Enhancing photocatalyst stability, optimizing solar-to-hydrogen efficiency, integrating renewable electricity, and valorizing oxygen as a coproduct can further improve environmental performance and cost-effectiveness. In comparison with the other solar and conventional methods, photocatalytic hydrogen is the most sustainable option, along with the perovskite/silicon photoelectrochemical alternative. The findings provide critical guidance for scaling up solar-driven hydrogen production and inform policy, research, and regional deployment strategies.
Abstract Water quality degradation and biological invasions represent major drivers of global ecosystem degradation, yet their interactive effects remain poorly understood, especially in anthropogenically disturbed estuarine ecosystems. Here, we employed environmental DNA (eDNA) metabarcoding to characterize multi-trophic biological communities in a subtropical estuary and to assess how water-quality degradation influences the invasion success of non-native fishes. The results show, firstly, the relative sequence abundance of non-native fish, rather than their species richness, emerged as the primary factor negatively associated with native fish diversity. Based on the observational dataset, we identified a statistical breakpoint, and the transition from low to high invasion pressure corresponds to a unimodal (hump-shaped) diversity pattern. Secondly, non-native fish primarily compete for food resources, thereby constraining the ecological niches of native species. Thirdly, a strong interactive effect exists between water quality degradation and non-native fish invasion. Water quality degradation acts not merely as a direct environmental stressor, but also indirectly weakens native communities. Collectively, these findings provide new insights into how declines in water quality interact with biological invasions and highlight the need for integrated invasion management strategies that simultaneously improve water quality and mitigate the impacts of invasive species in estuarine ecosystems.
Abstract The cardiopulmonary risks of fine particulate matter (PM2.5) are linked to its constituents, yet key constituents and underlying molecular pathways driving cardiopulmonary dysfunctions in older adults remain elusive. In a longitudinal panel study of 313 measurements, we assessed associations between PM2.5 constituents and cardiopulmonary functions and explored mediation effects by DNA methylation and gene transcription using personal monitoring data. We combined a linear mixed-effects model with three machine-learning methods to identify key PM2.5 constituents, and employed mediation analysis and Ingenuity Pathway Analysis to explore potential epigenetic and transcriptional mediators and biological pathways. Our findings revealed that chloride ion (Cl–), nickel (Ni), barium, and selenium were the key constituents of PM2.5 inducing cardiopulmonary dysfunction. Interquartile range (IQR) increases in Cl– and Ni were associated with a 3.48% (95% CI: 1.50%, 5.46%) increase in diastolic blood pressure and a 0.09% (95% CI: 0.05%, 0.12%) decrease in FEV1/FVC, respectively. Mediation analysis identified 212 cytosine-phosphate-guanine (CpG) sites that regulated both cardiovascular and pulmonary dysfunctions, and 7 genes mediating more than two distinct constituent-function associations. Neurotransmission, metabolism, and cardiovascular function-related pathways were primarily enriched, among which 22 CpG sites (e.g., cg07115148, cg26409134, and cg26613778) were identified as key epigenetic mediators. Expression quantitative trait methylation analysis revealed that these CpG sites were associated with 14 protein-coding genes including CERS6 and LRCH3. Our findings suggest that short-term exposure to PM2.5 constituents triggers cardiopulmonary dysfunctions via DNA methylation-gene transcription axes and related disruption of neurotransmission, metabolism, and cardiovascular signaling pathways.
