New particle formation (NPF) substantially affects air pollution and climate change. However, as an NPF hotspot, the mechanisms and impacts of NPF across broad spatial and temporal scales over China remain poorly understood, largely owing to the lack of critical NPF processes in atmospheric models. This study developed a comprehensive model that integrates 12 NPF mechanisms, including recent insights on various iodine-oxoacid-driven pathways and cluster-dynamics-based rate calculations. The updated model reduces model-observation discrepancies from around or over an order of magnitude to within ±30% across different sites and seasons. Simulations revealed that NPF over mainland China is driven primarily by sulfuric acid (H2SO4), dimethylamine (DMA), and iodic acid (HIO3). Importantly, H2SO4-DMA nucleation is not only the dominant mechanism in urban atmospheres, but also a major contributor in agricultural and forested regions. Differently, the HIO3-(H2SO4)-DMA mechanism contributes substantially in southeastern coastal areas, while iodine-oxoacid-H2SO4 pathways dominate in marine regions. High H2SO4 levels are identified as the main driver of eastern China's NPF hotspots, with temperature governing seasonal variations. Correspondingly, NPF contributes 10%-35% of cloud condensation nuclei (at 0.5% supersaturation) in the lower troposphere. Our models and findings support comprehensive understanding of NPF over China, and are also highly valuable for studying NPF in other regions with diverse emission sources and land cover types, and thereby contributing to accurate assessment of the environmental and climatic effects of aerosols.

Atmospheric sulfur-containing volatile organic compounds (sulfur-VOCs) have been recognized as crucial precursors for gaseous sulfuric acid (H2SO4), particulate sulfate and secondary organic aerosol (SOA) formation. However, their reaction kinetics and multi-sulfur product formation remain poorly understood. This study presents a systematic kinetic investigation into ⚫OH-initiated oxidation of a series of sulfur-VOCs including thiols and sulfides. The reaction rate constants vary with molecular structure, with high reactivity observed for trimethylene sulfide and dimethyl disulfide. It was further demonstrated that under low-NOx conditions, sulfur-containing RO2 radicals can undergo bimolecular reactions forming low-volatility multi-sulfur products that enhance their SOA formation potential. Additionally, many sulfur-VOCs investigated in our chamber experiments are also identified from the emissions of algae samples collected from a major freshwater lake in China, and similar multi-sulfur oxidation products were observed after ⚫OH oxidation. These findings advance the kinetic and mechanistic understanding of atmospheric sulfur-VOCs oxidation and suggest that the formation of low-volatility multi-sulfur products and inorganic sulfur-containing species may contribute to SOA production and new particle formation in marine and freshwater environments influenced by algal emissions.

Abstract. Atmospheric new particle formation (NPF) supplies up to half of global cloud condensation nuclei, yet the growth of sub-15 nm nanoparticles—the stage most vulnerable to scavenging—remains poorly constrained, largely because the volatility of oxygenated organic molecules (OOMs) is highly uncertain. Using a purpose-built laminar flow reactor that isolates particle–particle coagulation from OOM condensation, we show that six of seven widely used OOM volatility parameterizations substantially overestimate nanoparticle growth rates, with the largest bias under the high-NOx conditions. A recent parameterization constrained by ambient organic aerosol volatility reproduces our laboratory observations across diverse OOM precursors, seed sizes (3–5 nm), and NOx regimes. By applying this laboratory-validated framework to NPF events at Lake Tai, China, in summer 2023, OOM and H2SO4 condensation explain about 53 % of the observed 3–15 nm growth rate, leaving a residual that persists even at the upper bound of measurement uncertainty. Together, our laboratory experiments and field observations provide strong evidence that particle coagulation and vapour condensation alone cannot account for ambient nanoparticle growth, revealing a clear gap in our understanding of this process. This gap may point to additional processes, not yet accounted for in current frameworks, that could contribute to nanoparticle growth in polluted atmospheres, or it may reflect uncertainties in other parameters.

BACKGROUND:Air quality improvements have reduced PM2.5 mass, but particle surface area, which primarily contributes to inflammatory responses, may not follow the same trend, potentially creating health-relevant exposure. METHODS:To investigate this potential decoupling, we analyzed three years of observations in Fuzhou, China. Potential inflammatory responses were estimated from the lung-deposited surface area (LDSA) exceeding PM2.5-based expectations, using an animal-derived dose-response relationship that relates particle surface area to pulmonary inflammation. RESULTS:We identified that 6.6% of PM2.5 attainment hours (<35 μg m-3) exhibited elevated LDSA, with surface area exposure 7.5-fold greater than expected from the LDSA/PM2.5 ratio during other attainment hours, and 82% of potential inflammatory risk was undetected by mass-based assessment. During these periods, despite median PM2.5 mass concentrations of only 3.0 μg m-3 (well below air quality standards), toxicological dose-response assessment predicts potentially clinically relevant inflammatory responses (27% lung neutrophil infiltration). Machine learning reveals that photochemical oxidation (elevated O3 and secondary organic carbon importance) contributes to these periods by producing abundant 50-100 nm particles during summer-autumn afternoons under warm, high-radiation conditions. CONCLUSIONS:These photochemical ultrafine particle events represent a mechanistically distinct pollution regime where mass-based frameworks may underestimate potential inflammatory effects, a gap that may widen as emission controls reduce primary sources and climate warming enhances photochemistry.

Achieving high charging efficiencies for sub-10 nm aerosol particles is essential for accurate measurements of particle composition and concentration. In this study, we developed a novel, simple unipolar dielectric barrier discharge (DBD) charger to efficiently charge sub-10 nm aerosol particles without by-product formation. We optimized the charger operational parameters, including ion separation voltage and discharge frequency, and evaluated the charger’s performance in terms of particle penetration and charging efficiency. Our results show a high particle penetration efficiency (> 90%) across the sub-10 nm size range, with particle losses being predominantly governed by diffusion mechanisms and negligible electrostatic effects. At an aerosol flowrate of 6.5 L min-1, the extrinsic charging efficiency for 3 nm and 10 nm was approximately 11% and 60%, respectively. When used for particle number size distribution measurements, this unipolar charger provides a raw signal intensity that is up to 8.5 times higher on average than an X-ray source across the measured particle size range, which reduces inversion uncertainties with fewer spikes. Although highly-purity helium discharge gas is used to produce ions, which may increase the operational costs, the developed unipolar charger achieves a high-efficiency charging for sub-10 nm particles, offering a promising solution for sub-10 nm particle charging, detection and measurements.

P-Phenylenediamines (PPDs), widely used tire antioxidants, undergo oxidation to form toxic quinones (PPD-Qs). Despite their detection in diverse environmental media, the role of cloud water in environmental fate remains unknown. This study employed ultrahigh-performance liquid chromatography-Orbitrap mass spectrometry to investigate ten PPDs and PPD-Qs in cloud water collected from Tianmu Mountain in China─a remote background site with minimal industrial/human activity. The concentrations of PPDs (3.0-43.7 ng/L) are markedly exceeding their transformation products (PPD-Qs, 0.2-11.5 ng/L), with IPPD and 6PPD dominating. PPDs exhibited greater accumulation in water-insoluble organic matter (WISOM) than in water-soluble organic matter (WSOM), with enrichment factors (concentration of PPDs in WISOM/concentration of PPDs in WSOM) ranging from 1.13 to 1.88, indicating a stronger tendency for particle-phase partitioning. Significant positive correlations linked PM2.5 levels with the deposition fluxes of both PPDs and PPD-Qs in WSOM and WISOM, demonstrating cloud water's key role in their atmospheric transport and wet deposition. This study presents the first characterization of PPDs and their quinone derivatives' distribution and environmental behavior in cloud water, revealing clouds' significant role in the fate of rubber-derived pollutants. The findings reveal clouds as pivotal reactors for tire-derived pollutants, driving oxidation and multiphase portioning, previously overlooked in global contaminant cycling.

Aerosol particles, profoundly influenced by human activities, play pivotal roles in air quality and climate. The formation and growth of new atmospheric particles is a leading source of high-concentration aerosol particles in urban environments and also the largest source of uncertainties in global climate predictions. Recent advances in experimental and theoretical research have dramatically improved our understanding of urban new particle formation (NPF), showing that the abundant anthropogenic pollutants in complex urban atmospheres enable the fast formation of new particles that are highly selective toward the gaseous precursors and chemical processes. The uniqueness of urban atmospheres causes the underrepresentation of urban NPF in regional and global models, while the evolving urban environments complicate the prediction of future environmental and climate effects of NPF. In this review, we link the latest molecular-level chemical mechanisms and implications on climate predictions and air pollution control by assessing the methodology to investigate urban NPF, sorting out the latest mechanistic findings, and discussing their implementation in three-dimensional models.

Abstract New particle formation has been estimated to produce more than half of the global cloud condensation nuclei and profoundly impacts clouds, climate, and air quality. The initial growth from the cluster size ( ~ 1 nm) to a few nanometers, for which the underlying mechanisms can be very different from the subsequent growth, is the most critical stage for new particles to become climate-relevant. However, initial growth mechanisms evidenced by controlled laboratory experiments can rarely explain observations from the real atmosphere. Here we show that a large nanoparticle concentration gradient in the size space can drive unexpected rapid initial growth based on measurements across the globe. It accelerates the condensation of globally abundant oxygenated organic molecules onto a population of new particles compared to a single particle, and substantially increases the fraction of new particles that survive to climate- and air-quality-relevant sizes. Our findings provide insights into explaining the puzzle of the frequent new particle formation events in polluted urban environments and indicate an even more important role of new particle formation in climate predictions.

The invasive Spartina alterniflora is rapidly expanding along China's southeast coast, profoundly altering wetland soil properties, and methane (CH4) fluxes. However, the mechanism underlying the relationship between these environmental changes triggered by the invasion and the variations in CH4 emissions remain to be further deeply explored. We compared S. alterniflora-invaded wetlands with native Cyperus malaccensis wetlands through a one-year field monitoring and complementary laboratory experiments. The findings indicate that S. alterniflora invasion markedly decreased soil bulk density (4.3%) and increased water content (7.5%), while altering bacterial communities, notably increasing Microbulbifer (165.3%) and decreasing Anaeromyxobacter (61.7%) relative abundances. Consequently, cumulative soil CH4 emissions significantly increased by 354.9%, whereas CH4 emission temperature sensitivity (Q10) decreased by 79.8% (p < 0.05). CH4 emissions were positively correlated with the content of mineral-associated organic carbon (MAOC), dissolved organic carbon (DOC), total nitrogen (TN), soil temperature, and Microbulbifer abundance. Conversely, CH4 emissions were negatively related to clay content, particulate organic carbon (POC), and the abundances of Anaeromyxobacter. Q10 values were primarily influenced by soil texture, nutrient levels (TN, TP), MBC, and Microbulbifer abundance. Our findings indicate that the encroachment of S. alterniflora increases CH4 emissions while decreasing their Q10 by modifying soil physicochemical conditions, influenced by its plant traits. These findings highlight the critical need to manage S. alterniflora expansion to mitigate coastal wetland greenhouse gas emissions.

Fully automated instruments for in-situ aerosol collection and thermal desorption (CTD) have been developed and applied to atmospheric aerosol characterization, particularly the Thermal Desorption Aerosol GC-MS (TAG) and FIGAERO-CIMS for speciated organic composition. However, the TAG still encounters challenges such as high component costs, cumbersome hard-plumbed connections and transfer-efficiency losses during extended operation. To address these challenges, we present a low-cost inlet, fully automated instrument featuring a soft connection with only a 10-cm injection needle and a pair of septa between the CTD cell and the GC inlet. When collecting aerosol samples, the injection needle tip is placed in the gap between the pair of septa. During thermal desorption, the needle passes through the second septum and enters the GC inlet for sample introduction. At a CTD temperature of 350 degrees C, thermal-desorption relative transfer efficiencies for C-13-C-40 alkanes ranged from 33% to 154% relative to GC direct injection. Empirical detection limits were <= 0.05 ng per compound for C-13-C-16 alkanes, 0.05-1 ng up to C-40 alkanes, <= 0.5 ng for decanoic and undecanoic acids,1-5 ng for octadecanoic acid, and 5-10 ng for levoglucosan, comparable to those reported for TAG and up to an order of magnitude lower for several C-20-C-36 alkanes. This design requires no GC modifications, maintains efficient and stable transfer efficiency, and achieves low detection limits with an instrument build cost of only a few thousand dollars.

Saturation vapor pressure of atmospheric organic compounds is crucial for understanding gas-particle partitioning. Yet measurements of such a property are quite incomplete, and an accurate and efficient volatility parametrization remains challenging. Here, we utilized a Long Time-of-Flight Chemical Ionization Mass Spectrometer (LToF-CIMS) coupled with a Filter Inlet for Gases and Aerosols (FIGAERO) to measure molecular composition and saturation vapor pressure of organic compounds on particulate samples collected from Dianshan Lake and Tai Lake, China across different seasons with a wide temperature coverage. Two desorption procedures, i.e., a high-temperature range of 20-160 degrees C and a low-temperature range of 5-35 degrees C, were implemented. The obtained saturation vapor pressures of organic components were integrated with previous results (Yang et al., 2023) to compose our data set. By incorporating the concept of mole fraction (X) and addressing data imbalance across different volatility bins via Synthetic Minority Oversampling (SMOTE) and Random Under-sampling (RUS), a 4-parameter volatility parametrization of a commonly used volatility formula was developed, which outperforms previous ones for volatility prediction of both CHO and CHON compounds when validated against the NCI database, and potentially improves atmospheric models that use volatility as a key input. Atmospheric gas-particle partitioning is critical for environmental assessment. Using real atmospheric particle data, this study advances volatility parametrization of VOCs, and improves atmospheric model simulations and environmental impact evaluations.

Abstract Volatile organic compounds (VOCs) are receiving more attention for their potential to form ozone and secondary organic aerosol (SOA). Considerable amounts of VOCs are released from freshwater algae, and their chemical compositions and release rates have not been well understood. In this work, chemical compositions and release rates of VOCs emitted from a dominant algae species ( Microcystis aeruginosa ) in freshwater phytoplankton community were investigated under various cultivation conditions (i.e., BG11 medium, BG11 + extra nitrogen nutrient, BG11 + extra phosphorus nutrient, and low pH). 238 VOC species were identified from the emission of M. aeruginosa , among which 40 were hydrocarbons (elemental composition: CH), 81 were oxygenated‐VOCs (elemental composition: CHO), 61 were nitrogen‐containing VOCs (elemental composition: CHN and CHNO), 56 were sulfur‐containing VOCs (elemental composition: CHS, CHSO, CHNS, CHNSO). The average release rates of hydrocarbons, oxygenated‐VOCs (CHO), sulfur‐VOCs (CHS and CHSO), and nitrogen‐VOCs (CHN and CHNO) across all cultivation conditions were 668.6 ± 431.6, 352.0 ± 244.7, 2562.5 ± 1347.3, and 12.3 ± 5.76 ng·m −2 ·h −1 , respectively, among which, sulfur‐VOCs were the dominant species. Adding NH 4 Cl or CO(NH 2 ) 2 as extra nitrogen nutrient significantly reduced total VOCs release. Hydrocarbons and nitrogen‐VOCs were mainly released during the growth stage of algae, while some oxygenated species and sulfur‐containing species were released during the decline phase. This study offers enhanced insight into the diversity and emission levels of VOCs produced by freshwater algae and underlying SOA and ozone formation over and around inland eutrophic lakes.

Limiting global warming below 1.5 or 2 °C calls for achieving energy systems with net-zero carbon dioxide (CO2) emissions likely by 2040 or 2070, but the pledged actions under current policies cannot meet these targets. Few studies have optimized global deployment of photovoltaic and wind power. Here we present a strategy involving construction of 22,821 photovoltaic, onshore-wind, and offshore-wind plants in 192 countries worldwide to minimize the levelized cost of electricity. We identify a large potential of cost reduction by combining coordination of energy storage and power transmission, dynamics of learning, trade of minerals, and development of supply chains. Our optimization increases the capacity of photovoltaic and wind power, accompanied by a reduction in the average cost of abatement from US Dollars ($) 140 (baseline) to $33 per tonne CO2. Our study provides a global roadmap for achieving energy systems with net-zero CO2 emissions, emphasizing the physical, financial, and socioeconomic challenges forward.

Machine learning (ML) models have been widely utilized for the prediction of ground-level ozone (O3), one of the most concerning air pollutants in China. However, many of the ML models tend to underestimate high O3 levels, likely due to the class imbalance issue within the input training data. In this study, we combined data from ground monitoring stations (CO, NO2, SO2, PM10, PM2.5, MDA8 O3, longitude, and latitude), satellite observations (HCHO column concentration) and meteorological variables (2m temperature, solar radiation, relative humidity, wind components, surface pressure, precipitation, evaporation, boundary layer height, and cloud cover) to assess the impact of data imbalance on prediction performance. Results demonstrated that ML models without considering data imbalance issue severely underestimate high O3 levels. We proposed a sample weighting-based support vector regression model (SVR-W) that fully considered the data imbalance. Based on data from 2026 monitoring stations across 31 provinces in China, the SVR-W model achieved an average bin-slope value between observed and predicted O3 of 0.74 +/- 0.12 (s.d.), which is significantly better than commonly used ML models (0.64 +/- 0.11). The average bin-RMSE of the SVR-W model was 26.7 mu g/m3, outperforming other models. The average recall of high O3 levels was 11-31% higher than commonly used ML models. The SVR-W model demonstrated improved prediction performance for both regular and extreme pollutant O3 levels based on the three metrics. Our findings suggest that addressing data imbalance is crucial when applying ML models to environmental data.

Nitrogen-containing organic compounds (NOCs) in frost serve as a critical pathway for atmospheric nitrogen deposition, significantly impacting the biogeochemical cycles of nitrogen. However, the molecular characteristics of NOCs in frost and their deposition fluxes are scarcely studied. In this work, frost samples, collected in rural Northeast China in the winter of 2023, were analyzed using nontargeted ultrahigh performance liquid chromatography-orbitrap mass spectrometry (UHPLC-Orbitrap MS) to reveal their content in nitrogen-containing organic compounds (NOCs) and explore their wet deposition fluxes. The average number of assigned molecular formulas were lager on hazy days compared to nonhazy days for both water-soluble (WSOM) and water-insoluble organic matter (WISOM) in frost (3114 vs. 1934 for WSOM and 3042 vs. 2224 for WISOM in electrospray ionization (ESI-); 6921 vs. 5954 for WSOM and 6629 vs. 5547 in ESI+). Specifically, the number proportions of CHON were 35.6-49.9% (724-1517) and 47-51.1% (2686-3388) in the ESI- and ESI+ modes, respectively. Nitrophenol (C6H5NO3) and methyl nitrophenol (C7H7NO4) were the most abundant NOCs, with wet deposition fluxes (at maximum average concentrations) of 22.2 and 21.2 μg m-2·h-1, respectively. On hazy days, the deposition fluxes of nitrophenol compounds reached up to 1.73 times that of nonhazy days, indicating significant ambient nitrogen deposition during the haze episode. This deposition flux positively correlated with PM2.5 concentration, implying the important role of atmospheric particulates in influencing NOC deposition through frost. These findings highlight the susceptibility of frost to capturing NOCs from the atmosphere, potentially impacting nitrogen cycling in ecosystems.