Hydrothermal carbonization demonstrates a potential for converting invasive plants into multifunctional carbonaceous material. Invasive plant-based hydrochar derived dissolved organic matter (HDOM) becomes an important source of anthropogenic dissolved organic matter, however, the molecular composition and bioavailability of HDOM and the controlling factors were not sufficiently revealed. Thus, in this study, a variety of invasive plants were selected to fabricate hydrochar at different hydrothermal temperatures to investigate the molecular composition via FT-ICR-MS and bioavailability based on microbial fuel cell system. The results indicated dissolved organic carbon (DOC) yield peaked at 200°C and pH fluctuated within a range of 5.0 ‒ 6.0. Along with the increase in hydrothermal temperature, macromolecular humic-like substances promoted via depolymerization, dehydration, and condensation of lignocellulose, likewise unsaturated-reduced molecules as well as the diversity of CHO group in HDOMs. Van Krevelen diagrams demonstrated highly unsaturated and phenolic compounds as lignin-like/CRAMs were the dominant components. Biomass feedstocks did not greatly alter the molecular distribution pattern of HDOMs. HDOMs were introduced into the microbial fuel cell system as the substitute carbon source of sodium acetate, according to the output voltage, HDOMs demonstrated a superior bioavailability, and the effects of biomass feedstocks and hydrothermal temperature were in line with the percentage of labile compounds (MLBL%). HDOMs may serve as a carbon substrate that upregulated catabolic pathways to enhance the bioavailability, and act as metabolic driver to promote the nitrogen removal efficiency via enhancing denitrification and anammox. Environmental implications of HDOMs based on molecular composition and bioavailability were further discussed. This work provided theoretical foundation for optimizing the hydrothermal carbonization of invasive plants and reducing the ecological risks of invasive plant-based hydrochar.

Marine dissolved organic matter (DOM) represents a primary reservoir in the biogeochemical cycle, and marine microorganisms are essential to the transformation and long-term sequestration of DOM as recalcitrant dissolved organic matter (RDOM). In China's marginal seas, DOM levels are affected by coastal productivity and terrestrial inputs, yet the molecular mechanisms driving the DOM to RDOM transformation remain insufficiently characterized. This study aimed to elucidate the mechanisms behind the DOM transformation mediated by marine microorganisms in the Bohai and Yellow Seas, particularly focusing on molecular-level characterizations of microbial carbon cycling processes. Here, using 16S rDNA amplicon sequencing, we analyzed the bacterial communities across the surface and deep layers. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used to molecularly characterize the DOM. Our findings revealed distinct bacterial diversity and functional profiles between the surface and deep layers, with deep layers exhibiting higher microbial diversity. Furthermore, the deep layers were characterized by higher proportions of RDOM, with molecular indicators such as carboxyl-rich alicyclic molecules (CRAM) suggesting enhanced carbon stability. This study highlights the role of microbial processes in shaping the molecular characteristics of DOM across depths, supporting the microbial carbon pump (MCP) framework and characterizing the Bohai and Yellow Seas as significant carbon sinks in the coastal region. These findings advance our mechanistic understanding of oceanic carbon sequestration, particularly in coastal marginal seas.

Groundwater nitrate pollution is increasingly severe, creating a significant stoichiometric imbalance between carbon and nitrogen. Yet, how dissolved organic carbon-to-nitrate ratios (DOC:NO3⁻) regulate dissolved organic matter (DOM) composition, microbial community structure, and nitrogen transformation remains unclear, especially in oligotrophic aquifers with scarce carbon sources. By integrating Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and high-throughput quantitative PCR (HT-qPCR), we elucidated the effects of DOC:NO3⁻ on DOM composition and nitrogen cycling. Our results revealed that extreme carbon limitation in the LDN group (low dissolved organic carbon-to-nitrate ratio, DOC:NO3⁻ < 0.1) promoted the selective preservation and accumulation of humic-like DOM. The LDN group contained more unique molecular formulas than the HDN group (0.1 ≤ DOC:NO3⁻ < 1.0) (1194 vs 848), predominantly distributed in the highly unsaturated structures with high oxygen region, suggesting greater humification and structural complexity under persistent carbon limitation. Moreover, the microbial co-occurrence network in the LDN group showed higher connectivity with more positive associations than that in the HDN group, implying greater reliance on metabolic cross-feeding to overcome energy constraints. Notably, denitrification genes were 1.98 times more abundant in the LDN group than in the HDN group (P < 0.05), suggesting a robust potential for nitrogen removal despite the low DOC availability. Partial least squares structural equation modeling (PLS-SEM) further identified DOM composition and microbial community structure as key drivers of nitrogen reduction functions. These findings challenge the conventional view that only labile carbon supports denitrification, demonstrating instead that humic-like DOM may serve as a persistent carbon reservoir and potential redox mediator to sustain nitrogen cycling in carbon-limited groundwater. This study provides a new mechanistic perspective for nitrate pollution control and the management of deep subsurface ecosystems.

Abstract Accurate estimation of crude oil viscosity is crucial for formulating optimal hydrocarbon recovery strategies. Nuclear magnetic resonance (NMR) is a non-destructive technique for viscosity characterization with a longitudinal and transverse relaxation times (T₁ and T₂), diffusion coefficient, or apparent hydrogen index derived from ¹H signals. In this review, the theoretical methods for crude oil viscosity characterization with NMR are systematically sorted, which is crucial for novices and petroleum engineers. First, the basic principles of NMR are introduced, and the theoretical basis of NMR-based crude oil viscosity characterization is described in terms of relaxation times, diffusion coefficient, and apparent hydrogen index. Then, a systematic review is conducted for NMR-based crude oil viscosity characterization method developed over the past three decades. Finally, four kinds of influence factor—instrument parameters, temperature, crude oil type, and gas oil ratio—are analyzed. The results emphasize the importance of selecting a suitable viscosity model based on reservoir type and formation conditions. Two-dimensional NMR T1−T2 techniques demonstrate potential for addressing crude oil viscosity characterization challenges. In general, the key to crude oil viscosity characterization with NMR is selecting the appropriate NMR method rationally based on clear reservoir characteristics. This study aims to assess the existing methods and their limitations critically while providing guidance toward more robust viscosity quantification protocols.

Hydrothermal liquefaction (HTL) is an effective pathway for the high-value utilization of food waste (FW); however, the resulting bio-oil is typically enriched with heteroatom-containing compounds that severely limit its subsequent upgrading and utilization. Although solvent regulation has been widely recognized as an efficient strategy for improving bio-oil quality, the solvent-directed evolution behavior of N-, O-, and S-containing species during HTL remains insufficiently understood at the molecular level. In this study, FW was subjected to HTL in pure water (WE-10), water–ethanol mixture (WE-12), and pure ethanol (WE-01) systems. Electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR MS) was employed to systematically characterize the compositional evolution of heteroatom species in bio-oil. The results showed that solvent composition strongly influenced heteroatom evolution tendencies and compositional complexity of the resulting bio-oils. Under the WE-10 condition, highly oxygenated compounds were significantly enriched, particularly O₄–O₆ and N₁O₃–₆ species, accompanied by broad DBE and molecular-mass distributions as well as increased molecular polarity. In contrast, WE-01 favored the enrichment of low-O aromatic heterocyclic compounds, leading to simplified compositional distributions and reduced oxygenation states. The WE-12 system exhibited transitional evolution characteristics between WE-10 and WE-01, maintaining moderate oxygenation levels while preserving relatively broad compositional diversity. Notably, N–O–S coupling species were significantly enriched in ethanol-containing systems, suggesting enhanced heteroatom interactions during molecular evolution. These coupled heteroatom formulas contributed to the molecular-level compositional complexity of FW-derived bio-oil. Based on the molecular-level characterization results, a solvent-directed heteroatom evolution model was proposed. Water-rich systems favored oxidative growth and accumulation of highly oxygenated structures, whereas ethanol-rich environments promoted reductive stabilization and selective evolution toward low-O aromatic compounds. This study provides molecular-level guidance for solvent engineering toward targeted heteroatom regulation and production of high-quality bio-oils from FW through HTL.

The growing demand for sustainable and efficient proppants in unconventional oil and gas development has driven interest in biomass-based alternatives to conventional high-density materials. This study proposes a low-density proppant derived from sawdust, a widely available byproduct of the wood processing industry. Through wettability modification involving hydrophilic and hydrophobic treatments, the sawdust fragments exhibited improved interfragment bonding, compressive strength, and acid resistance. The modified proppant achieved an ultralow apparent density of 0.16 g cm-3 and demonstrated favorable transportability in water without additional chemical additives, reducing the need for high-viscosity thickeners and minimizing formation damage. Under closure stress, the modified sawdust compacted into dense support pillar structures, maintaining fracture conductivity while forming layered flow channels conducive to hydrocarbon migration. This innovative approach not only enhances the mechanical performance and transport behavior of modified sawdust pillar proppants but also highlights the potential of lignocellulosic waste valorization in hydraulic fracturing applications. Ultimately, this work demonstrates a cost-effective and eco-friendly solution that aligns with the growing emphasis on environmental responsibility and sustainable energy practices in hydraulic fracturing operations.

BACKGROUND:Atmospheric particulate matter (PM) is a complex mixture with a wide range of sources, but only a limited proportion can be identified by existing analytical techniques. Comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS) couples the advantages on high resolution, sensitivity, and peak capacity on gas chromatography, together with the high mass accuracy and acquisition frequency of time-of-flight mass spectrometry (TOFMS). GC × GC-MS has been gradually applied on the analysis of environmental organic pollutants. AIMS:This review introduces the principles of GC × GC together with MS and discusses its application on organic compounds in atmospheric PM in the last two decades, so as to provide an outlook on the future trends of GC × GC-MS in this research frontiers. MATERIALS AND METHODS:The review synthesizes findings on the application of GC × GC-MS for analyzing organic pollutants in PM, covering its operational principles and the coupling with TOFMS to enhance mass accuracy and acquisition speed. RESULTS:GC × GC-MS has significantly improved the identification of PM-associated organic compounds by offering superior separation, peak capacity, and detection sensitivity. The technique has enabled the discovery of previously unresolvable compounds and enhanced source apportionment of PM. DISCUSSION:Despite its analytical advantages, the widespread application of GC × GC-MS in atmospheric studies is hindered by challenges such as complex data processing, instrument cost, and standardization issues. CONCLUSION:GC × GC-MS offers superior separation and identification of complex pollutants, making it invaluable for environmental analysis and applications. Emerging technologies, such as machine learning, will enhance its analytical capabilities and broaden its future applications.

While dam-based regulation modifies the natural transport rhythm of riverine materials, the effects of artificial flooding on river mouth dissolved organic matter (DOM) dynamics remain poorly constrained. The Water-Sediment Regulation Scheme in the Yellow River provides a unique snapshot. Distinct organic matter signatures were observed between the water release and sediment flushing phases using optical and molecular techniques. Here we show that during water release phase, rapid discharge of upper-layer water from Xiaolangdi Reservoir increased the proportion of bio-labile DOM in the Yellow River mouth. Conversely, during sediment flushing phase, resuspension and then release of bottom sediments from the reservoir enhanced aromatic DOM components. Although the relative abundance and composition of particulate organic matter remained unchanged during water release phase, it increased during sediment flushing phase. These findings demonstrate that reservoir operations reconfigure river-ocean carbon flows, emphasizing the need to integrate dam management strategies into global carbon cycling models. During water release, rapid discharge of upper-layer water from Xiaolangdi Reservoir increased bio-labile dissolved organic matter at the Yellow River mouth, while sediment flushing resuspended bottom sediments and enhanced aromatic components, as shown by optical spectroscopy and isotope analysis.

Reactive iron oxides, as an efficient "rust sink" for organic carbon, play a pivotal role in the long-term preservation of organic carbon within global soils. Although coastal wetlands are crucial carbon sinks on Earth, the composition of reactive iron-bound organic carbon (FeR-OC) remain unclear. In this study, we applied a modified citrate-bicarbonate-dithionite (CBD) extraction method coupled with advanced analytical techniques including optical spectroscopy, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and stable isotope mass spectrometry to investigate FeR-OC in the Yellow River coastal wetland in China. Our findings reveal that the FeR-OC:FeR ratios are relatively low (0.1-0.8), suggesting that adsorption is the primary mechanism controlling FeR-OC formation in the Yellow River coastal wetland. Correlation analysis between FeR content and fluorescence components indicates that iron oxides preferentially adsorb biologically recalcitrant humic-like components, while exhibiting limited affinity for protein-like. Meanwhile, we identified 1440 dissolved organic matter (DOM) molecules adsorbed by iron oxides, predominantly by oxygen-rich and highly unsaturated molecules. Furthermore, the FeR-OC content in vegetated areas is an order of magnitude higher than bare flat, indicating that the restoration of vegetation is effective strategy for enhancing carbon sequestration in coastal wetlands. This study bridges laboratory simulations with natural samples, establishing a novel protocol enables more precise understanding of Fe-C coupling in real environments.

Seasonal dynamics of dissolved organic matter (DOM) in agricultural ditches significantly impact carbon cycling and water quality in connected rivers. This study aimed to characterize seasonal variations in DOM composition and dynamics within hierarchical agricultural ditch systems in Tianjin, northern China. Surface water samples were collected from river channels, main ditches, branch ditches, lateral ditches, and field ditches during wet (June 2021) and dry (December 2021) seasons. DOM characteristics were analyzed using dissolved organic carbon (DOC) quantification, ultraviolet-visible (UV-Vis) absorption spectroscopy, and three-dimensional excitation–emission matrix spectroscopy (3D-EEMs) coupled with parallel factor analysis (PARAFAC). The concentration of DOC in ditch surface water exhibited significant seasonal variations, with significantly higher levels observed during the wet season (Huangzhuang: 6.72 ± 0.7 mg/L; Weixing: 13.15 ± 3.1 mg/L) compared to the dry season (Huangzhuang: 5.93 ± 0.3 mg/L; Weixing: 9.35 ± 2.6 mg/L). Both UV-Vis spectral and EEM-PARAFAC analysis revealed that DOM in ditch systems was predominantly composed of fulvic-like and tryptophan-like components, representing the portion of organic matter in water bodies that is highly biologically active, highly mobile, relatively “fresh”, or “not fully humified”. PARAFAC identified microbial humic-like (C1: wet season 40.36%, dry season 34.42%) and protein-like (C3: wet season 40.3%, dry season 49.87%) components as dominant. DOM sources were influenced by dual inputs from terrestrial and autochthonous origins during the wet season, while primarily deriving from autochthonous sources in the dry season. This study elucidates the advances of spectroscopic techniques in deciphering the composition, sources, and influencing factors of DOM in aquatic systems. The findings support implementing riparian buffer strips and optimized fertilizer management to mitigate seasonal peaks of bioavailable DOM in agricultural ditch systems.

The overwintering recovery of Microcystis aeruginosa represents a critical but underexplored phase in the seasonal development of cyanobacterial blooms. Although the role of temperature in driving bloom onset is recognized, its effects on microbial assembly and the molecular transformation of dissolved organic matter during reactivation remain insufficiently characterized. In this study, 16S rRNA gene sequencing, excitation-emission matrix fluorescence spectroscopy coupled with parallel factor analysis, Fourier transform ion cyclotron resonance mass spectrometry, and metabolomics were applied to examine how three thermal recovery regimes-constant temperature, gradual warming, and cold-dark preconditioning-shape microbial succession and dissolved organic matter dynamics. Constant temperature accelerated the dispersal limitation of bacterial communities and promoted rapid dissolved organic matter (DOM) turnover, whereas gradual warming and cold-dark preconditioning induced more undominated community structures, and the accumulation of nitrogen- and sulfur-rich DOM compounds. Cold-dark pretreatment notably enhanced the formation of structurally complex, recalcitrant DOM, and delayed microbial reactivation. The network of relationships between microorganisms and dissolved organic matter revealed distinct coupling patterns across treatments, with enhanced microbial processing of aromatic and humic-like molecules occurring under thermal fluctuation or stress. Metabolomic profiling further indicated different physiological adaptation strategies, with stress-linked metabolites enriched under variable-temperature conditions. These findings highlight the mechanistic links between temperature-driven microbial recovery and dissolved organic matter transformation, providing new insights into how winter conditions influence cyanobacterial bloom trajectories in freshwater ecosystems.

RATIONALE:Dissolved organic nitrogen (DON) is a crucial component in environment, which acts as the largest reservoir of nitrogen and plays a significant role in the nitrogen cycling, pollutant transport, and substrate utilization among various environmental systems. DON exhibits a relatively low concentration in environment, which presents a great challenge for DON detection, and an efficient separation and enrichment lab protocol is required to fully understand its structural and compositional characteristics. However, there is no standard method to extract DON from complex environmental samples efficiently. METHODS:The DON was extracted utilizing solid-phase extraction (SPE), with a one-step elution by the Bond Elut PPL cartridge and the Waters HLB cartridge, and a three-step elution by the Waters MCX cartridge. UV-Vis, fluorescence, mass spectrometry (MS), and gas chromatography-nitrogen chemiluminescence detector (GC-NCD) techniques were utilized to investigate and compare the characteristics of DON from the three different SPE strategies. RESULTS:Combined the fluorescence and MS results, it is found that the stepwise extraction using the MCX cartridge exhibits the best recovery of DON for both standard and environmental samples, and its performance is less affected by the chemical interferences such as surfactants during MS analysis. Furthermore, the MCX fraction exhibits the highest number of DON molecular formulas with a low O/C ratio and a high H/C ratio in environmental samples, and such a fraction also shows an enrichment of nitrosamine-type substances. CONCLUSIONS:This work establishes an efficient MCX-SPE protocol to extract and analyze DON, which can be applied to environmental samples straightforward. The presented work provides a theoretical support for the analysis of DON, which facilitates a comprehensive understanding of the chemical composition and environmental effect of nitrogen-containing substances.

Nitrogen-containing organic compounds (NOCs) emitted from biomass combustion contribute significantly to air pollution, yet their comprehensive characterization remains limited. In this study, NOCs in PM2.5 derived from combustion of pine wood and wheat straw were characterized using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) coupled with six ionization modes, including electrospray ionization positive (+ESI) and negative (-ESI) modes, matrix-assisted laser desorption/ionization positive (+MALDI) and negative (-MALDI) modes, atmospheric-pressure photoionization positive mode (+APPI), and atmospheric-pressure chemical ionization positive mode (+APCI). This study marks the first application of FT-ICR MS with six ionization modes for biomass-combustion-derived PM2.5 characterization. We have successfully established a more comprehensive formula inventory for CHON molecules, including 7486 from pine wood combustion and 8341 from wheat straw combustion. These represent increases of 55.4-717% and 42.3-424%, respectively, compared to the numbers of formulas detected by the individual ionization modes. Furthermore, NOCs with varying oxidation states and volatilities exhibit distinct detection performance across the six ionization modes, offering deeper insights into their characteristics and enhancing the data support for the interpretation of atmospheric chemical processes.

Effective management of chemical reagents in universities is essential for laboratory safety and operational efficiency. Manual management models characterized by fragmented oversight are insufficient to ensure traceability, real-time monitoring, and safety compliance, as evidenced by the recurring occurrence of laboratory safety accidents. In this study, we propose an intelligent management model for college-level chemical reagent repositories. The model was built on a Laboratory Information Management System (LIMS)-based architecture and modified using Internet of Things (IoT) sensing, Radio Frequency Identification (RFID), and intelligent hardware. It transforms the full-lifecycle of reagents (from procurement and storage to distribution, usage, and waste disposal) into a digital, automated, closed-loop process. In addition, this study also highlights key technical challenges, including heterogenous system integration and reliable data acquisition under complex environmental conditions, and proposes practical strategies, such as lightweight Application Programming Interface (API) middleware. The results show that the proposed model is a feasible and robust framework for precise, proactive, and data-driven management of hazardous chemicals in academic settings.

Dissolved organic matter (DOM) plays important roles in the global carbon cycle and aquatic ecosystem health. Estuaries are critical zones connecting land and ocean in which DOM experiences dispersion, transformation, degradation, deposition, etc. The Water-sediment regulation scheme (WSRS) was implemented in Yellow River (YR) and approximately half of annually sediment and a quarter of annually water were poured into estuary in around 20 days. Meanwhile, huge amounts of DOM were discharged into Yellow River estuary (YRE) rapidly, but their processes and fates in YRE and adjacent seas are unclear. This study aims to investigate the molecular and spectrum compositions of DOM and its associated transformation mechanisms around the YRE and its adjacent sea before (from June 8 to 12, 2022) and after (from July 18 to 22, 2022) the WSRS. A relatively greater amount of highly unsaturated compounds and terrestrial-derived DOM was found with higher aromaticity and humification degree after WSRS, by bulk geochemical techniques, optical spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) techniques. High levels of less photodegraded DOM were found in the estuarine region after WSRS, due to the rapidly pouring huge amount of fresh water and sediment into YRE. The high suspended sediment concentration facilitates the sorption of dissolved organic carbon (DOC), especially those sulphur-containing compounds in DOM which decreased both in the relative intensity and number. However, in the long term, WSRS may lead to an increase of DOC in the water column. Along with the YR plume and coastal current, DOM was transported from the YRE to Laizhou Bay to the south and arrived at Bohai Strait to the east. Overall, this research provides valuable insights into estuary DOM variations induced by the intensive dam-orientated regulation in a short term.

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) has greatly promoted an understanding of the complex chemical composition of petroleum-derived samples. Relying on this analytical instrument, along with pretreatment methods such as component separation, virtually comprehensive approaches for petroleum molecular composition analysis have been established in the past two decades. However, for certain samples, specific pretreatments and instrumental settings may be required for FT-ICR MS analysis. In this study, specific compound species, including Na1O2S2, Na1O4S1, N1O 2S1, and Na1O1S1, that are not commonly found in petroleum were identified in two high-sulfur-content crude oils using positive-ion electrospray ionization (+ESI) FT-ICR MS. Collision-induced dissociation (CID) was employed to further characterize these species, and they were confirmed to be sulfoxide-derived adducts. Ionization additives and broadband CID were combined, enabling the elimination of all types of adduct ions. Additionally, the crude oils were separated into multiple subfractions by a chromatographic column with cross-polarity elution, and the subfractions were analyzed separately incorporating the proposed adduct elimination method. High-condensation O1S1 class species, which had not been detected in direct analysis, were identified in subfractions. The adduct ion elimination method and the cross-polarity chromatographic approach demonstrated great applicability across different crude oils, providing a viable strategy for the correct classification of compound types and the identification of components that had been overlooked due to matrix effect and ionization suppression.

The property of groundwater dissolved organic matter (DOM) subjected to anthropogenic groundwater recharge (AGR) might be affected by the water quality disparity between surface water and natural groundwater. However, the diverse molecular scenarios of groundwater DOM under uneven recharging levels remain largely unexplored. We combined molecular characteristics, carbon isotopic signatures of organic molecules, and end-member mixing analysis to explore the sensitivity and potential tracking capabilities of DOM to AGR along with recharging gradients. Our findings suggested that AGR enriched groundwater with diverse, saturated, labile, and sulfur-rich molecules, amplifying DOM abundance and intensity, which intensified with recharge gradients. Additionally, S-containing molecules and their indicators like CHOS% (with threshold values of 7.82%) exhibited high sensitivity and predictive power for AGR recognition. The major signatures (diversity, saturated degree, and stability) indicated by 13C-containing molecules were similar to the whole molecular pool. Notably, specific molecules (C12H10O5S and C15H16O12), although not detected in all groundwater samples, exhibit robust stability or favorable solubility, rendering them potential candidates as AGR-sensitive molecules. The R13C/12C ratio of 13C-containing C19H24O5 emerged as the most robust tracer, exhibiting a strong correlation with the recharge ratio and the smallest deviation from the theoretical mixing line, signifying its optimal suitability for precise groundwater DOM source apportionment. This study offers novel insights into AGR impacts and contributes to fostering a harmonious balance between human activities and water resource sustainability.

RationaleThe sources and chemical compositions of organic aerosol (OA) exert a significant influence on both regional and global atmospheric conditions, thereby having far-reaching implications on environmental chemistry. However, existing mass spectrometry (MS) methods have limitations in characterizing the detailed composition of OA due to selective ionization as well as fractionation during cold-water extraction and solid-phase extraction (SPE).MethodsA comprehensive MS study was conducted using aerosol samples collected on dusty, clean, and polluted days. To supplement the data obtained from electrospray ionization (ESI), a strategy for analyzing OAs collected using the quartz fiber filter directly utilizing laser desorption ionization (LDI) was employed. Additionally, the ESI method was conducted to explore suitable approaches for determining various OA compositions from samples collected on dusty, clean, and polluted days.ResultsIn situ LDI has the advantages of significantly reducing the sample volume, simplifying sample preparation, and overcoming the problem of overestimating sulfur-containing compounds usually encountered in ESI. It is suitable for the characterization of highly unsaturated and hydrophobic aerosols, such as brown carbon-type compounds with low volatility and high stability, which is supplementary to ESI.ConclusionsCompared with other ionization methods, in situ LDI helps provide a complementary description of the molecular compositions of OAs, especially for analyzing OAs in polluted day samples. This method may contribute to a more comprehensive MS analysis of the elusive compositions and sources of OA in the atmosphere.