Fine-mode aerosol optical depth (fAOD) is a vital proxy for the concentration of anthropogenic aerosols in the atmosphere. Currently, the limited data length and high uncertainty of the satellite-based data diminish the applicability of fAOD for climate research. Here, we propose a novel pretrained deep learning framework that can extract information underlying each satellite pixel and use it to create new latent features that can be employed for improving retrieval accuracy in regions without in situ data. With the proposed model, we developed a new global fAOD (at 0.5 μm) data from 2001 to 2020, resulting in a 10% improvement in the overall correlation coefficient (R) during site-based independent validation and a 15% enhancement in non-AERONET site areas validation. Over the past two decades, there has been a noticeable downward trend in global fAOD (-1.39 × 10-3/year). Compared to the general deep-learning model, our method reduces the global trend\'s previously overestimated magnitude by 7% per year. China has experienced the most significant decline (-5.07 × 10-3/year), which is 3 times greater than the global trend. Conversely, India has shown a significant increase (7.86 × 10-4/year). This study bridges the gap between sparse in situ observations and abundant satellite measurements, thereby improving predictive models for global patterns of fAOD and other climate factors.

Airborne microplastics (MPs) are important pollutants that have been present in the environment for many years and are characterized by their universality, persistence, and potential toxicity. This study investigated the effects of terrestrial and marine transport of MPs in the atmosphere of a coastal city and compared the difference between daytime and nighttime. Laser direct infrared imaging (LDIR) and polarized light microscopy were used to characterize the physical and chemical properties of MPs, including number concentration, chemical types, shape, and size. Backward trajectories were used to distinguish the air masses from marine and terrestrial transport. Twenty chemical types were detected by LDIR, with rubber (16.7%) and phenol-formaldehyde resin (PFR; 14.8%) being major components. Three main morphological types of MPs were identified, and fragments (78.1%) are the dominant type. MPs in the atmosphere were concentrated in the small particle size segment (20-50 µm). The concentration of MPs in the air mass from marine transport was 14.7 items/m3 - lower than that from terrestrial transport (32.0 items/m3). The number concentration of airborne MPs was negatively correlated with relative humidity. MPs from terrestrial transport were mainly rubber (20.2%), while those from marine transport were mainly PFR (18%). MPs in the marine transport air mass were more aged and had a lower number concentration than those in the terrestrial transport air mass. The number concentration of airborne MPs is higher during the day than at night. These findings could contribute to the development of targeted control measures and methods to reduce MP pollution.

To explore air contamination resulting from special biomass combustion and suspended dust in Lhasa, the present study focused on the size distribution and chemical characteristics of particulate matter (PM) emission resulting from 7 types of non-fossil pollution sources. We investigated the concentration and size distribution of trace elements from 7 pollution sources collected in Lhasa. Combining Lhasa\'s atmospheric particulate matter data, enrichment factors (EFs) have been calculated to examine the potential impact of those pollution sources on the atmosphere quality of Lhasa. The highest mass concentration of total elements of biomass combustion appeared at PM0.4, and the second highest concentration existed in the size fraction 0.4-1 µm; the higher proportion (12 %) of toxic metals was produced by biomass combustion. The elemental composition of suspended dust and atmospheric particulate matter was close (except for As and Cd); the highest concentration of elements was all noted in PM2.5-10 (PM3-10). Potassium was found to be one of the main biomass markers. The proportion of Cu in suspended dust is significantly lower than that of atmospheric particulate matter (0.53 % and 3.75 %), which indicates that there are other anthropogenic sources. The EFs analysis showed that the Cr, Cu, Zn, and Pb produced by biomass combustion were highly enriched (EFs > 100) in all particle sizes. The EFs of most trace elements increased with decreasing particle size, indicating the greater influence of humanfactors on smaller particles.

The chemistry of sulfur cycle contributes significantly to the atmospheric nucleation process, which is the first step of new particle formation (NPF). In the present study, cycloaddition reaction mechanism of sulfur trioxide (SO3) to hydrogen sulfide (H2S) which is a typical air pollutant and toxic gas detrimental to the environment were comprehensively investigate through theoretical calculations and Atmospheric Cluster Dynamic Code simulations. Gas-phase stability and nucleation potential of the product thiosulfuric acid (H2S2O3, TSA) were further analyzed to evaluate its atmospheric impact. Without any catalysts, the H2S + SO3 reaction is infeasible with a barrier of 24.2 kcal/mol. Atmospheric nucleation precursors formic acid (FA), sulfuric acid (SA), and water (H2O) could effectively lower the reaction barriers as catalysts, even to a barrierless reaction with the efficiency of cis-SA > trans-FA > trans-SA > H2O. Subsequently, the gas-phase stability of TSA was investigated. A hydrolysis reaction barrier of up to 61.4 kcal/mol alone with an endothermic isomerization reaction barrier of 5.1 kcal/mol under the catalytic effect of SA demonstrates the sufficient stability of TSA. Furthermore, topological and kinetic analysis were conducted to determine the nucleation potential of TSA. Atmospheric clusters formed by TSA and atmospheric nucleation precursors (SA, ammonia NH3, and dimethylamine DMA) were thermodynamically stable. Moreover, the gradually decreasing evaporation coefficients for TSA-base clusters, particularly for TSA-DMA, suggests that TSA may participate in NPF where the concentration of base molecules are relatively higher. The present new reaction mechanism may contributes to a better understanding of atmospheric sulfur cycle and NPF.

Heterogeneous oxidation by gas-phase oxidants is an important chemical transformation pathway of secondary organic aerosol (SOA) and plays an important role in controlling the abundance, properties, as well as climate and health impacts of aerosols. However, our knowledge on this heterogeneous chemistry remains inadequate. In this study, the heterogeneous oxidation of α-pinene ozonolysis SOA by hydroxyl (OH) radicals was investigated under both low and high relative humidity (RH) conditions, with an emphasis on the evolution of molecular composition of SOA and its RH dependence. It is found that the heterogeneous oxidation of SOA at an OH exposure level equivalent to 12 hr of atmospheric aging leads to particle mass loss of 60% at 25% RH and 95% at 90% RH. The heterogeneous oxidation strongly changes the molecular composition of SOA. The dimer-to-monomer signal ratios increase dramatically with rising OH exposure, in particular under high RH conditions, suggesting that aerosol water stimulates the reaction of monomers with OH radicals more than that of dimers. In addition, the typical SOA tracer compounds such as pinic acid, pinonic acid, hydroxy pinonic acid and dimer esters (e.g., C17H26O8 and C19H28O7) have lifetimes of several hours against heterogeneous OH oxidation under typical atmospheric conditions, which highlights the need for the consideration of their heterogeneous loss in the estimation of monoterpene SOA concentrations using tracer-based methods. Our study sheds lights on the heterogeneous oxidation chemistry of monoterpene SOA and would help to understand their evolution and impacts in the atmosphere.

The photolysis of particulate nitrate (pNO3-) has been suggested to be an important source of nitrous acid (HONO) in the troposphere. However, determining the photolysis rate constant of pNO3- (jpNO3-) suffers from high uncertainty. Prior laboratory measurements of jpNO3- using aerosol filters have been complicated by the \"shadow effect\"─a phenomenon of light extinction within aerosol layers that potentially skews these measurements. We developed a method to correct the shadow effect on the photolysis rate constant of pNO3- for HONO production (jpNO3- → HONO) using aerosol filters with identical chemical compositions but different aerosol loadings. We applied the method to quantify jpNO3- → HONO over the North China Plain (NCP) during the winter haze period. After correcting for the shadow effect, the normalized average jpNO3- → HONO at 5 °C increased from 5.89 × 10-6 s-1 to 1.72 × 10-5 s-1. The jpNO3- → HONO decreased with increasing pH and nitrate proportions in PM2.5 and had no correlation with nitrate concentrations. A parametrization for jpNO3- → HONO was developed for model simulation of HONO production in NCP and similar environments.

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Atmospheric microplastics are important contributors to environmental contamination in aquatic and terrestrial systems and pose potential ecological risks. However, studies on atmospheric microplastics are still limited in urban regions of the Tibetan Plateau, a sentinel region for climate and environmental change under a warming climate. In this study, the occurrence and potential ecological risk of atmospheric microplastics were investigated in samples of suspended atmospheric microplastics collected in Lhasa city during the Tibetan New Year in February 2023. The results show that the average abundance of atmospheric microplastics in Lhasa was 7.15 ± 2.46 MPs m-3. The sizes of the detected microplastics ranged from 20.34 to 297.18 μm, approximately 87% of which were smaller than 100 μm. Fragmented microplastics (95.76%) were the dominant shape, followed by fibres (3.75%) and pellets (0.49%). The primary polymer chemical components identified were polyamide (68.73%) and polystyrene (16.61%). The analysis of meteorological data and the backwards trajectory model indicated the air mass in Lhasa mainly controlled by westwards, and the atmospheric microplastics mainly originated from long-distance atmospheric transport. The potential ecological risk index assessment revealed that the atmospheric microplastic pollution in Lhasa was relatively low. This study provides valuable insights and a scientific foundation for future research on the prevention and control of atmospheric microplastic pollution in Lhasa and other ecologically sensitive cities.

Heavy metal accumulation in agricultural products has become a major concern. Previous studies have focused on the transport of heavy metals from the soil and their accumulation in crops. However, recent studies revealed that wheat leaves, ears, and awns can also transport and accumulate heavy metals. Wheat grains can be influenced by two sources of heavy metals: soil contamination and atmospheric deposition. To comprehend the transport characteristics of heavy metals in soil, atmospheric deposition, and wheat, 37 samples each for wheat rhizosphere soil, wheat roots, stems, leaves, and grains were collected. Fifteen samples of atmospheric dry deposition and atmospheric wet deposition were collected from Linshu County (northern area), China. Based on the test data, the characteristics of heavy metals and their distribution in the study area were analyzed. Migration patterns of heavy metals in crops from different sources were investigated using Pearson correlation and redundancy analysis. Finally, a predictive model for heavy metals in wheat grains was developed using multiple linear regression analysis. Significant disparities in the distribution of heavy metals existed among wheat roots, stems, leaves, and grains. The coefficient of variation of heavy metals in atmospheric deposition was relatively high, indicating discernible spatial patterns influenced by human activities. Notably, a positive correlation was observed between the concentration of heavy metals in wheat grains and atmospheric deposition of Hg, Cd, and Pb. Conversely, Zn and Ni levels in wheat grains were significantly negatively associated with soil Zn, Ni, pH, and OM content. The contribution of heavy metal elements from different sources varied in their impact on the grain\'s heavy metal content. Specifically, atmospheric deposition was the primary source of Hg and Pb in wheat grains, while Cd, Ni, Cu, and Zn were predominantly derived from soil. Using a multiple linear regression model, we could accurately predict Hg, Pb, Cd, Ni, Zn, and As concentrations in crop grains. This model can facilitate quantitative evaluation of ecological risk of heavy metals accumulation in crops in the study area.

Global climate zones are experiencing widespread shifts with ongoing rise in atmospheric CO2, influencing vegetation growth and shifting its distributions to challenge ecosystem structure and function, posing threats on ecological and societal safety. However, how rising atmospheric CO2 affects the pace of global climate zone shifts is highly uncertain. More attentions are urgently required to understand the underlying mechanisms and quantifications of regional climate vulnerability in response to rising CO2. In this study, we employ nine Earth system models from CMIP6 to investigate global climate zone shifts with rising CO2, unravel the effects of vegetation physiological response (PHY), and categorize climate vulnerable regions depending on the extent of climate zone shifts. We find that climate zone shifts over half of the global land area, 16.8% of which is contributed by PHY at 4 × CO2. Intriguingly, besides warming, PHY-induced precipitation changes and their interactions with warming dominate about two-fifths of PHY-forced shifts, providing potential direction for model improvement in future predictions of climate zone shifts. Aided with PHY effects, 4 × CO2 imposes substantial climate zone shifts over about one-fifth of the global land area, suggesting substantial changes in local climate and ecosystem structure and functions. Hence, those regions would experience strong climate vulnerability, and face high risk of climate extremes, water scarcity and food production. Our results quantitatively identify the vulnerable regions and unravel the underlying drivers, providing scientific insights to prioritize conservation and restoration efforts to ensure ecological and social safety globally.