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Black carbon (BC) in the Tibetan Plateau (TP) region has distinct climate effects that strongly depend on its mixing state. The aging processes of BC in the TP are subject to emissions from various regions, resulting in considerable variability of its mixing state and physicochemical properties. However, the mechanism and magnitude of this effect are not yet clear. In this study, field observations on physicochemical properties of BC-containing particles (PMBC) were conducted in the northeast (Xihai) and southeast (Lulang) regions of the TP to investigate the impacts of transported emissions from lower-altitude areas on BC characteristics in the TP. Large spatial discrepancies were found in the chemical composition of PMBC. Both sites showed higher concentrations of PMBC when they were affected by transported air masses outside the TP but with diverse chemical composition. Source apportionment for organic aerosol (OA) suggested that primary OA in the northeastern TP was attributed to hydrocarbon OA (HOA) from anthropogenic emissions, while it was dominated by biomass burning OA (BBOA) in the southeastern TP. Regarding secondary aerosol, a marked enhancement in nitrate fraction was observed on aged BC coating in Xihai when the air masses were brought by updrafts and easterly winds from lower-altitude areas. With the development of boundary layer, the enhanced turbulent mixing promoted the elevation of anthropogenic pollutants. In contrast to Xihai, the thickly coated BC in Lulang was mainly caused by elevation and transportation of biomass burning plumes from south Asia, showing a large contribution of secondary organic aerosol (SOA). The distinct transported emissions lead to substantial variations of both chemical composition and light absorption ability of BC across the TP. The thicker coating and higher mass absorption cross-section (MAC) of PMBC in air masses elevated from lower-altitude regions reveal the promoted BC aging processes and their impacts on the mixing state and light absorption of BC in the TP. These findings emphasize the vulnerability of plateau regions to influences of elevated emissions, leading to significant changes in BC concentration, mixing states and light absorption across the TP, all of which need to be considered in the evaluation of BC radiative effects for the TP region.

New particle formation (NPF) is a major source of aerosol particles and cloud condensation nuclei in the troposphere, playing an important role in both air quality and climate. Frequent NPF events have been observed in heavily polluted urban environments, contributing to the aerosol number concentration by a significant amount. The Po Valley region in northern Italy has been characterized as a hotspot for high aerosol loadings and frequent NPF events in southern Europe. However, the mechanisms of NPF and growth in this region are not completely understood. In this study, we conducted a continuous 2-month measurement campaign with state-of-the-art instruments to elucidate the NPF and growth mechanisms in northern Italy. Our results demonstrate that frequent NPF events (66 % of all days during the measurement campaign) are primarily driven by abundant sulfuric acid (8.5×106 cm−3) and basic molecules in this area. In contrast, oxygenated organic molecules from the atmospheric oxidation of volatile organic compounds (VOCs) appear to play a minor role in the initial cluster formation but contribute significantly to the consecutive growth process. Regarding alkaline molecules, amines are insufficient to stabilize all sulfuric acid clusters in the Po Valley. Ion cluster measurements and kinetic models suggest that ammonia (10 ppb) must therefore also play a role in the nucleation process. Generally, the high formation rates of sub-2 nm particles (87 cm−3 s−1) and nucleation-mode growth rates (5.1 nm h−1) as well as the relatively low condensational sink (8.9×10-3 s−1) will result in a high survival probability for newly formed particles, making NPF crucial for the springtime aerosol number budget. Our results also indicate that reducing key pollutants, such as SO2, amine and NH3, could help to substantially decrease the particle number concentrations in the Po Valley region.

Early growth of atmospheric particles is essential for their survival and ability to participate in cloud formation. Many different atmospheric vapors contribute to the growth, but even the main contributors still remain poorly identified in many environments, such as high-altitude sites. Based on measured organic vapor and sulfuric acid concentrations under ambient conditions, particle growth during new particle formation events was simulated and compared with the measured particle size distribution at the Chacaltaya Global Atmosphere Watch station in Bolivia (5240 m a.s.l.) during April and May 2018, as a part of the SALTENA (Southern Hemisphere high-ALTitude Experiment on particle Nucleation and growth) campaign. Despite the challenging topography and ambient conditions around the station, the simple particle growth model used in the study was able to show that the detected vapors were sufficient to explain the observed particle growth, although some discrepancies were found between modeled and measured particle growth rates. This study, one of the first of such studies conducted on high altitude, gives insight on the key factors affecting the particle growth on the site and helps to improve the understanding of important factors on high-altitude sites and the atmosphere in general. Low-volatility organic compounds originating from multiple surrounding sources such as the Amazonia and La Paz metropolitan area were found to be the main contributor to the particle growth, covering on average 65 % of the simulated particle mass in particles with a diameter of 30 nm. In addition, sulfuric acid made a major contribution to the particle growth, covering at maximum 37 % of the simulated particle mass in 30 nm particles during periods when volcanic activity was detected on the area, compared to around 1 % contribution on days without volcanic activity. This suggests that volcanic emissions can greatly enhance the particle growth.

Air ions are the key components for a series of atmospheric physicochemical interactions, such as ion-catalyzed reactions, ion-molecule reactions, and ion-induced new particle formation (NPF). They also control atmospheric electrical properties with effects on global climate. We performed molecular-level measurements of cluster ions at the high-altitude research station Chacaltaya (CHC; 5240 m a.s.l.), located in the Bolivian Andes, from January to May 2018 using an atmospheric-pressure-interface time-of-flight mass spectrometer. The negative ions mainly consisted of (H2SO4)0–3⚫HSO4-, (HNO3)0–2⚫NO3-, SO5-, (NH3)1–6⚫(H2SO4)3–7⚫HSO4-, malonic-acid-derived, and CHO / CHON⚫(HSO4- / NO3-) cluster ions. Their temporal variability exhibited distinct diurnal and seasonal patterns due to the changes in the corresponding neutral species' molecular properties (such as electron affinity and proton affinity) and concentrations resulting from the air masses arriving at CHC from different source regions. The positive ions were mainly composed of protonated amines and organic cluster ions but exhibited no clear diurnal variation. H2SO4–NH3 cluster ions likely contributed to the NPF process, particularly during the wet-to-dry transition period and the dry season, when CHC was more impacted by air masses originating from source regions with elevated SO2 emissions. Our study provides new insights into the chemical composition of atmospheric cluster ions and their role in new particle formation in the high-altitude mountain environment of the Bolivian Andes.

Dimethyl sulfide (DMS) is the primary natural contributor to the atmospheric sulfur burden. Observations concerning the fate of DMS oxidation products after long-range transport in the remote free troposphere are, however, sparse. Here we present quantitative chemical ionization mass spectrometric measurements of DMS and its oxidation products sulfuric acid (H2SO4), methanesulfonic acid (MSA), dimethylsulfoxide (DMSO), dimethylsulfone (DMSO2), methanesulfinic acid (MSIA), methyl thioformate (MTF), methanesulfenic acid (MSEA, CH3SOH), and a compound of the likely structure CH3S(O)2OOH in the gas phase, as well as measurements of the sulfate and methanesulfonate aerosol mass fractions. The measurements were performed at the Global Atmosphere Watch (GAW) station Chacaltaya in the Bolivian Andes located at 5240 m above sea level (a.s.l.). DMS and DMS oxidation products are brought to the Andean high-altitude station by Pacific air masses during the dry season after convective lifting over the remote Pacific ocean to 6000–8000 m a.s.l. and subsequent long-range transport in the free troposphere (FT). Most of the DMS reaching the station is already converted to the rather unreactive sulfur reservoirs DMSO2 in the gas phase and methanesulfonate (MS−) in the particle phase, which carried nearly equal amounts of sulfur to the station. The particulate sulfate at Chacaltaya is however dominated by regional volcanic emissions during the time of the measurement and not significantly affected by the marine air masses. In one of the FT events, even some DMS was observed next to reactive intermediates such as methyl thioformate, dimethylsulfoxide, and methanesulfinic acid. Also for this event, back trajectory calculations show that the air masses came from above the ocean (distance >330 km) with no local surface contacts. This study demonstrates the potential impact of marine DMS emissions on the availability of sulfur-containing vapors in the remote free troposphere far away from the ocean.

New particle formation (NPF) is a significant source of atmospheric particles, affecting climate and air quality. Understanding the mechanisms involved in urban aerosols is important to develop effective mitigation strategies. However, NPF rates reported in the polluted boundary layer span more than 4 orders of magnitude, and the reasons behind this variability are the subject of intense scientific debate. Multiple atmospheric vapours have been postulated to participate in NPF, including sulfuric acid, ammonia, amines and organics, but their relative roles remain unclear. We investigated NPF in the CLOUD chamber using mixtures of anthropogenic vapours that simulate polluted boundary layer conditions. We demonstrate that NPF in polluted environments is largely driven by the formation of sulfuric acid–base clusters, stabilized by the presence of amines, high ammonia concentrations and lower temperatures. Aromatic oxidation products, despite their extremely low volatility, play a minor role in NPF in the chosen urban environment but can be important for particle growth and hence for the survival of newly formed particles. Our measurements quantitatively account for NPF in highly diverse urban environments and explain its large observed variability. Such quantitative information obtained under controlled laboratory conditions will help the interpretation of future ambient observations of NPF rates in polluted atmospheres.

Gaseous hydrochloric (HCl) and hydrobromic acid (HBr) are vital halogen species that play essential roles in tropospheric physicochemical processes. Yet, the majority of the current studies on these halogen species were conducted in marine or coastal areas. Detection and source identification of HCl and HBr in inland urban areas remain scarce, thus limiting the full understanding of halogen chemistry and potential atmospheric impacts in the environments with limited influence from the marine sources. Here, both gaseous HCl and HBr were concurrently measured in urban Beijing, China, during winter and early spring of 2019. We observed significant HCl and HBr concentrations ranging from a minimum value at 1 × 108 molecules cm−3 (4 ppt) and 4 × 107 molecules cm−3 (1 ppt) up to 6 × 109 molecules cm−3 (222 ppt) and 1 × 109 molecules cm−3 (37 ppt), respectively. The HCl and HBr concentrations are enhanced along with the increase of atmospheric temperature, UVB and levels of gaseous HNO3. Based on the air mass analysis and high correlations of HCl and HBr with the burning indicators (HCN and HCNO), gaseous HCl and HBr are found to be related to anthropogenic burning aerosols. The gas–particle partitioning may also play a dominant role in the elevated daytime HCl and HBr. During the daytime, the reactions of HCl and HBr with OH radicals lead to significant production of atomic Cl and Br, up to 2 × 104 molecules cm−3 s−1 and 8 × 104 molecules cm−3 s−1, respectively. The production rate of atomic Br (via HBr + OH) is 2–3 times higher than that of atomic Cl (via HCl + OH), highlighting the potential importance of bromine chemistry in the urban area. On polluted days, the production rates of atomic Cl and Br are faster than those on clean days. Furthermore, our observations of elevated HCl and HBr may suggest an important recycling pathway of halogen species in inland megacities and may provide a plausible explanation for the widespread halogen chemistry, which could affect the atmospheric oxidation in China.

Nucleation of atmospheric vapours produces more than half of global cloud condensation nuclei and so has an important influence on climate. Recent studies show that monoterpene (C10H16) oxidation yields highly oxygenated products that can nucleate with or without sulfuric acid. Monoterpenes are emitted mainly by trees, frequently together with isoprene (C5H8), which has the highest global emission of all organic vapours. Previous studies have shown that isoprene suppresses new-particle formation from monoterpenes, but the cause of this suppression is under debate. Here, in experiments performed under atmospheric conditions in the CERN CLOUD chamber, we show that isoprene reduces the yield of highly oxygenated dimers with 19 or 20 carbon atoms – which drive particle nucleation and early growth – while increasing the production of dimers with 14 or 15 carbon atoms. The dimers (termed C20 and C15, respectively) are produced by termination reactions between pairs of peroxy radicals (RO2⚫) arising from monoterpenes or isoprene. Compared with pure monoterpene conditions, isoprene reduces nucleation rates at 1.7 nm (depending on the isoprene ∕ monoterpene ratio) and approximately halves particle growth rates between 1.3 and 3.2 nm. However, above 3.2 nm, C15 dimers contribute to secondary organic aerosol, and the growth rates are unaffected by isoprene. We further show that increased hydroxyl radical (OH⚫) reduces particle formation in our chemical system rather than enhances it as previously proposed, since it increases isoprene-derived RO2⚫ radicals that reduce C20 formation. RO2⚫ termination emerges as the critical step that determines the highly oxygenated organic molecule (HOM) distribution and the corresponding nucleation capability. Species that reduce the C20 yield, such as NO, HO2 and as we show isoprene, can thus effectively reduce biogenic nucleation and early growth. Therefore the formation rate of organic aerosol in a particular region of the atmosphere under study will vary according to the precise ambient conditions.

Our understanding of atmospheric oxidation chemistry has improved significantly in recent years, greatly facilitated by developments in mass spectrometry. The generated mass spectra typically contain vast amounts of information on atmospheric sources and processes, but the identification and quantification of these is hampered by the wealth of data to analyze. The implementation of factor analysis techniques have greatly facilitated this analysis, yet many atmospheric processes still remain poorly understood. Here, we present new insights into highly oxygenated products from monoterpene oxidation, measured by chemical ionization mass spectrometry, at a boreal forest site in Finland in autumn 2016. Our primary focus was on the formation of accretion products, i.e., dimers. We identified the formation of daytime dimers, with a diurnal peak at noontime, despite high nitric oxide (NO) concentrations typically expected to inhibit dimer formation. These dimers may play an important role in new particle formation events that are often observed in the forest. In addition, dimers identified as combined products of NO3 and O3 oxidation of monoterpenes were also found to be a large source of low-volatility vapors at night. This highlights the complexity of atmospheric oxidation chemistry and the need for future laboratory studies on multi-oxidant systems. These two processes could not have been separated without the new analysis approach deployed in our study, where we applied binned positive matrix factorization (binPMF) on subranges of the mass spectra rather than the traditional approach where the entire mass spectrum is included for PMF analysis. In addition to the main findings listed above, several other benefits compared to traditional methods were found.

Highly oxygenated organic molecules (HOMs) from atmospheric oxidation of alpha-pinene can irreversibly condense to particles and contribute to secondary organic aerosol (SOA) formation. Recently, the formation of nitryl chloride (ClNO2) from heterogeneous reactions, followed by its subsequent photolysis, is suggested to be an important source of chlorine atoms in many parts of the atmosphere. However, the oxidation of monoterpenes such as alpha-pinene by chlorine atoms has received very little attention, and the ability of this reaction to form HOMs is completely unstudied. Here, chamber experiments were conducted with alpha-pinene and chlorine under low- and high-nitrogen-oxide (NOx, NOx=NO+NO2) conditions. A nitrate-based CI-APi-ToF (chemical ionization–atmospheric pressure interface–time of flight) mass spectrometer was used to measure HOM products. Clear distributions of monomers with 9–10 carbon atoms and dimers with 18–20 carbon atoms were observed under low-NOx conditions. With increased concentration of NOx within the chamber, the formation of dimers was suppressed due to the reactions of peroxy radicals with NO. We estimated the HOM yields from chlorine-initiated oxidation of alpha-pinene under low-NOx conditions to be around 1.8 %, though with a substantial uncertainty range (0.8 %–4 %) due to lack of suitable calibration methods. Corresponding yields at high NOx could not be determined because of concurrent ozonolysis reactions. Our study demonstrates that also the oxidation of alpha-pinene by chlorine atoms and yield low-volatility organic compounds.

Pyruvic acid (CH3C(O)C(O)OH, 2-oxopropanoic acid) is an organic acid of biogenic origin that plays a crucial role in plant metabolism, is present in tropospheric air in both gas-phase and aerosol-phase, and is implicated in the formation of secondary organic aerosols (SOAs). Up to now, only a few field studies have reported mixing ratios of gas-phase pyruvic acid, and its tropospheric sources and sinks are poorly constrained. We present the first measurements of gas-phase pyruvic acid in the boreal forest as part of the IBAIRN (Influence of Biosphere–Atmosphere Interactions on the Reactive Nitrogen budget) field campaign in Hyytiälä, Finland, in September 2016. The mean pyruvic acid mixing ratio during IBAIRN was 96 pptv, with a maximum value of 327 pptv. From our measurements we estimated the overall pyruvic acid source strength and quantified the contributions of isoprene oxidation and direct emissions from vegetation in this monoterpene-dominated forested environment. Further, we discuss the relevance of gas-phase pyruvic acid for atmospheric chemistry by investigating the impact of its photolysis on acetaldehyde and peroxy radical production rates. Our results show that, based on our present understanding of its photochemistry, pyruvic acid is an important source of acetaldehyde in the boreal environment, exceeding ethane and propane oxidation by factors of ∼10 and ∼20.

The outputs of four global climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5), which were statistically downscaled and bias corrected, were used to drive four hydrological models (Hydrologiska Byråns, HBV; Soil and Water Assessment Tool, SWAT; Soil and Water Integrated Model, SWIM; and Variable Infiltration Capacity, VIC) to simulate the daily discharge at the Cuntan hydrological station in the upper Yangtze River from 1861 to 2299. As the performances of hydrological models in various climate conditions could be different, the models were first calibrated in the period from 1979 to 1990. Then, the models were validated in the comparatively wet period, 1967–1978, and in the comparatively dry period, 1991–2002. A multi-objective automatic calibration programme using a univariate search technique was applied to find the optimal parameter set for each of the four hydrological models. The Nash–Sutcliffe efficiency (NSE) of daily discharge and the weighted least-squares function (WLS) of extreme discharge events, represented by high flow (Q10) and low flow (Q90), were included in the objective functions of the parameterization process. In addition, the simulated evapotranspiration results were compared with the GLEAM evapotranspiration data for the upper Yangtze River basin. For evaluating the performances of the hydrological models, the NSE, modified Kling–Gupta efficiency (KGE), ratio of the root-mean-square error to the standard deviation of the measured data (RSR) and Pearson's correlation coefficient (r) were used. The four hydrological models reach satisfactory simulation results in both the calibration and validation periods. In this study, the daily discharge is simulated for the upper Yangtze River under the preindustrial control (piControl) scenario without anthropogenic climate change from 1861 to 2299 and for the historical period 1861–2005 and for 2006 to 2299 under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios. The long-term daily discharge dataset can be used in the international context and water management, e.g. in the framework of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) by providing clues to what extent human-induced climate change could impact streamflow and streamflow trend in the future. The datasets are available at: https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc (Gao et al., 2019).

The formation of alkyl nitrates in various oxidation processes taking place throughout the diel cycle can represent an important sink of reactive nitrogen and mechanism for chain termination in atmospheric photo-oxidation cycles. The low-volatility alkyl nitrates (ANs) formed from biogenic volatile organic compounds (BVOCs), especially terpenoids, enhance rates of production and growth of secondary organic aerosol. Measurements of the NO3 reactivity and the mixing ratio of total alkyl nitrates (ΣANs) in the Finnish boreal forest enabled assessment of the relative importance of NO3-, O3- and OH-initiated formation of alkyl nitrates from BVOCs in this environment. The high reactivity of the forest air towards NO3 resulted in reactions of the nitrate radical, with terpenes contributing substantially to formation of ANs not only during the night but also during daytime. Overall, night-time reactions of NO3 accounted for 49 % of the local production rate of ANs, with contributions of 21 %, 18 % and 12 % for NO3, OH and O3 during the day. The lifetimes of the gas-phase ANs formed in this environment were on the order of 2 h due to efficient uptake to aerosol (and dry deposition), resulting in the transfer of reactive nitrogen from anthropogenic sources to the forest ecosystem.

Recent advancements in atmospheric mass spectrometry provide huge amounts of new information but at the same time present considerable challenges for the data analysts. High-resolution (HR) peak identification and separation can be effort- and time-consuming yet still tricky and inaccurate due to the complexity of overlapping peaks, especially at larger mass-to-charge ratios. This study presents a simple and novel method, mass spectral binning combined with positive matrix factorization (binPMF), to address these problems. Different from unit mass resolution (UMR) analysis or HR peak fitting, which represent the routine data analysis approaches for mass spectrometry datasets, binPMF divides the mass spectra into small bins and takes advantage of the positive matrix factorization's (PMF) strength in separating different sources or processes based on different temporal patterns. In this study, we applied the novel approach to both ambient and synthetic datasets to evaluate its performance. It not only succeeded in separating overlapping ions but was found to be sensitive to subtle variations as well. Being fast and reliable, binPMF has no requirement for a priori peak information and can save much time and effort from conventional HR peak fitting, while still utilizing nearly the full potential of HR mass spectra. In addition, we identify several future improvements and applications for binPMF and believe it will become a powerful approach in the data analysis of mass spectra.

The detailed formation mechanism of an increased number of haze events in China is still not very clear. Here, we found that reduced surface visibility from 1980 to 2010 and an increase in satellite-derived columnar concentrations of inorganic precursors from 2002 to 2012 are connected with each other. Typically, higher inorganic mass fractions lead to increased aerosol water uptake and light-scattering ability in elevated relative humidity. Satellite observation of aerosol precursors of NO2 and SO2 showed increased concentrations during the study period. Our in situ measurement of aerosol chemical composition in Beijing also confirmed increased contribution of inorganic aerosol fraction as a function of the increased particle pollution level. Our investigations demonstrate that the increased inorganic fraction in the aerosol particles is a key component in the frequently occurring haze days during the study period, and particularly the reduction of nitrate, sulfate and their precursor gases would contribute towards better visibility in China.

While the role of highly oxygenated molecules (HOMs) in new particle formation (NPF) and secondary organic aerosol (SOA) formation is not in dispute, the interplay between HOM chemistry and atmospheric conditions continues to draw significant research attention. During the Influence of Biosphere-Atmosphere Interactions on the Reactive Nitrogen budget (IBAIRN) campaign in September 2016, profile measurements of neutral HOMs below and above the forest canopy were performed for the first time at the boreal forest SMEAR II station. The HOM concentrations and composition distributions below and above the canopy were similar during daytime, supporting a well-mixed boundary layer approximation. However, much lower nighttime HOM concentrations were frequently observed at ground level, which was likely due to the formation of a shallow decoupled layer below the canopy. Near the ground HOMs were influenced by the changes in the precursors and oxidants and enhancement of the loss on surfaces in this layer, while the HOMs above the canopy top were not significantly affected. Our findings clearly illustrate that near-ground HOM measurements conducted under stably stratified conditions at this site might only be representative of a small fraction of the entire nocturnal boundary layer. This could, in turn, influence the growth of newly formed particles and SOA formation below the canopy where the large majority of measurements are typically conducted.

New particle formation (NPF) provides a large source of atmospheric aerosols, which affect the climate and human health. In recent chamber studies, ion-induced nucleation (IIN) has been discovered as an important pathway of forming particles; however, atmospheric investigation remains incomplete. For this study, we investigated the air anion compositions in the boreal forest in southern Finland for three consecutive springs, with a special focus on H2SO4-NH3 anion clusters. We found that the ratio between the concentrations of highly oxygenated organic molecules (HOMs) and H2SO4 controlled the appearance of H2SO4-NH3 clusters (3 no. S 2SO4] was smaller than 30. The number of H2SO4 molecules in the largest observable cluster correlated with the probability of ion-induced nucleation (IIN) occurrence, which reached almost 100 % when the largest observable cluster contained six or more H2SO4 molecules. During selected cases when the time evolution of H2SO4-NH3 clusters could be tracked, the calculated ion growth rates exhibited good agreement across measurement methods and cluster (particle) sizes. In these cases, H2SO4-NH3 clusters alone could explain ion growth up to 3 nm (mobility diameter). IIN events also occurred in the absence of H2SO4-NH3, implying that other NPF mechanisms also prevail at this site, most likely involving HOMs. It seems that H2SO4 and HOMs both affect the occurrence of an IIN event, but their ratio ([HOMs] ∕ [H2SO4]) defines the primary mechanism of the event. Since that ratio is strongly influenced by solar radiation and temperature, the IIN mechanism ought to vary depending on conditions and seasons.

Dinitrogen pentoxide (N2O5) and the nitrate radical (NO3) play important roles in atmospheric chemistry, yet accurate measurements of their concentrations remain challenging. A thermal dissociation chemical ionization mass spectrometer (TD-CIMS) was deployed to an urban site in Hong Kong to measure the sum of N2O5 and NO3 in autumn 2010 based on the signals of NO3− at 62 amu which has also been adopted in previous studies reported in literature. To our surprise, very large signals of N2O5 + NO3 were frequently observed at 62 amu in the daytime, with equivalent N2O5 + NO3 mixing ratios in the range of 200–1000 pptv. To investigate this unusual phenomenon, various interference tests and measurements with different instrument configuration were conducted. It was found that peroxy acetyl nitrate (PAN) contributed to measurable signals at 62 amu, and more importantly, this interference increased significantly with co-existence of NO2. Nitric acid (HNO3), on the other hand, had little interference to the detection of N2O5/NO3 via the NO3− ion in our TD-CIMS. According to the test results, the interference from PAN and NO2 could have contributed to 30–50% of the average daytime (12:00–16:00, local time) N2O5 + NO3 signal at our site. On the other hand, evidence exists for the presence of elevated daytime N2O5, in addition to the daytime signal at 62 amu. This includes (1) daytime N2O5 measured via the I(N2O5)− cluster ion with an unheated inlet, which was subjected to minimum interferences, and (2) observation of elevated daytime ClNO2 (a product of N2O5 hydrolysis) during a follow-up study. In view of the difficulty in accurately quantifying the contribution from the interferences of PAN and NO2 and untested potential interfering chemicals in the real atmosphere, we caution the use of 62 amu in the TD-CIMS for measuring ambient N2O5 in a high NOx environment like Hong Kong. Additional studies are needed to re-examine the daytime issue using other measurement techniques.

The troposphere plays an important role in a range of weather and various climate changes. With the development of the Global Navigation Satellite System (GNSS), the zenith tropospheric delay (ZTD) retrieval using GNSS technology has become a popular method. Research on ZTD accuracies of state-space representation (SSR) corrections from different analysis centers derived from real-time precise point positioning (RT-PPP) is important for Earth observation correction, meteorological disaster forecasting, and warning with the increasing abundance of state-space representation (SSR) products obtained by the International GNSS Service (IGS) analysis center. Therefore, accuracies and availability of real-time orbits and clock errors obtained by the Chinese Academy of Sciences (CAS), GMV Aerospace and Defense (GMV), Centre National d'Etudes Spatiales (CNE), and Wuhan University (WHU) are evaluated, and the RT positioning performance and ZTD accuracies are analyzed for Global Positioning System (GPS), Galileo (GAL), and BeiDou Navigation Satellite System-3 (BDS3) satellites. The results indicate that CAS has the higher satellite availability, providing SSR corrections for 82 GPS, Galileo, and BDS3 satellites. The accuracies of GPS, Galileo, and BDS3 orbits are best at WHU, CAS, and WHU with values of 5.57, 5.91, and 11.77 cm, respectively; the standard deviations (SDs) of clock error are all better than 0.22, 0.19, and 0.55 ns, and the root mean square errors (RMSEs) are better than 0.54, 0.32, and 1.46 ns. CAS has the best signal-in-space ranging errors (SISREs) followed by WHU, while CNE and GMV are worse. In the RT-PPP test, convergence times for CAS and WHU are 14.9 and 14.4 min, respectively, with 3D positioning accuracy for both of around 3.3 cm, which is better than for CNE and GMV. Among them, WHU SSR has the higher accuracy of RT-PPP-derived ZTD, with an RMSE of 6.06 mm and desirable availability with a completeness rate of 89 %.

Electromagnetic exploration, characterized by its low cost, wide applicability, and high operational efficiency, finds extensive applications in fields such as oil and gas exploration, mineral prospecting, and engineering geology. Traditional controlled-source electromagnetic detection methods are typically confined to operating frequencies below 250 kHz, resulting in insufficient detection accuracy for applications such as shallow- and intermediate-depth exploration, thereby constraining their performance in high-resolution imaging. To address these challenges, we propose a controlled-source ultrasonic audio frequency electromagnetic receive system based on the internet of things (IoT). We investigate cascaded digital filtering and sampling techniques to extend the receiver's sampling rate range, thereby elevating the operating frequency of controlled-source electromagnetic acquisition from the conventional maximum of 250 kHz to 1 MHz. The receiver achieves a sampling rate of up to 2.5 MHz, comprising three magnetic field measurement channels and two electric field measurement channels. The instrument is compact, lightweight, and capable of real-time data storage locally and real-time data transmission to an upper computer. Additionally, IoT technology is introduced, leading to the design of a cloud-based real-time remote control and data acquisition scheme. Experimental results demonstrate the stability of the instrument, meeting the requirements of field exploration.

We demonstrate how high spatial and temporal resolution spaceborne synthetic aperture radar (SAR) imagery can improve slope deformation monitoring. We process ICEYE data over the Brienz/Brinzauls slope instability in the Swiss Alps, where a catastrophic failure occurred on 15 June 2023. Image correlation applied to retrieve surface velocities shows results comparable to in situ measurements. Pre- and post-failure acquisitions used to map areas invaded by debris and to compute associated volumetric changes are in good agreement with photogrammetric data. This study sets the baseline for new-generation satellite SAR data aimed at providing timely information in landslide early warning scenarios.

Vehicles are among the most important contributors to global anthropogenic CO2 emissions. However, the lack of fuel-, vehicle-type-, and age-specific information about global on-road CO2 emissions in existing datasets, which are available only at the sector level, makes these datasets insufficient for supporting the establishment of emission mitigation strategies. Thus, a fleet turnover model is developed in this study, and CO2 emissions from global on-road vehicles from 1970 to 2020 are estimated for each country. Here, we analyze the evolution of the global vehicle stock over 50 years, identify the dominant emission contributors by vehicle and fuel type, and further characterize the age distribution of on-road CO2 emissions. We find that trucks accounted for less than 5 % of global vehicle ownership but represented more than 20 % of on-road CO2 emissions in 2020. The contribution of diesel vehicles to global on-road CO2 emissions doubled during the 1970–2020 period, driven by the shift in the fuel-type distribution of vehicle ownership. The proportion of CO2 emissions from vehicles in developing countries such as China and India in terms of global emissions from newly registered vehicles significantly increased after 2000, but global CO2 emissions from vehicles that had survived more than 15 years in 2020 still originated mainly from developed countries such as the United States and countries in the European Union. The data are publicly available at https://doi.org/10.6084/m9.figshare.24548008 (Yan et al., 2024).

With the rapid development of the world economy, China is becoming a key player in global trade and investment processes. Developing and updating legal rules governing contractual relations plays an important role in ensuring transparency, stability, and fairness in the business environment. Thus, the main purpose of this study was to identify the existing problems in the laws governing the process of contract cancellation and to make recommendations to improve the relevant aspects. In the course of the research, the legal method and the method of comparison were applied. As a result, the main procedures and grounds provided by the Civil Code of the People’s Republic of China for the termination of contractual obligations were identified. It was learnt that parties can terminate a contract in case of material breach of the terms of the agreement, which includes default, exceeding deadlines or changing circumstances that significantly affect the performance of the contract. The study also identified specific challenges that actors face when terminating contracts. Such as the unpredictability of the legal consequences of excluding a party from a contractual relationship, which can pose serious economic risks. The impact of factors such as economic crises on the termination of contractual obligations was also emphasised in the findings of the study. An important conclusion was the need to improve the legislation in the field of contract termination. The results of the study can be used to improve the law on contract termination in China, which can be the basis for developing clearer and more adaptive rules, thereby reducing possible legal risks for the business community

Light-absorbing carbonaceous aerosols are important contributors to both air pollution and radiative forcing. However, their abundances and sources remain poorly constrained, as can be seen from the frequently identified discrepancies between the observed and modeled results. In this study, we focused on elemental carbon (EC; as a measure of black carbon) and light-absorbing organic carbon (i.e., BrC) in Northeast China, a new targeted region of the latest clean-air actions in China. Three campaigns were conducted during 2018–2021 in Harbin, covering distinct meteorological conditions and emission features. Various analytical methods were first evaluated, and the mass concentrations of both BrC and EC were validated. The validated BrC and EC measurement results were then used for source apportionment, together with other species including tracers (e.g., levoglucosan). The observation-based results suggested that despite the frigid winter in Harbin, the formation of secondary organic carbon (SOC) was enhanced at high levels of relative humidity (RH). This enhancement could also be captured by an air quality model incorporating heterogeneous chemistry. However, the model failed to reproduce the observed abundances of SOC, with significant underestimations regardless of RH levels. In addition, agricultural fires effectively increased the observation-based primary organic carbon (POC) concentrations and POC to EC ratios. Such roles of agricultural fires were not captured by the model, pointing to substantial underestimation of open burning emissions by the inventory. This problem merits particular attention for Northeast China, given its massive agricultural sector.

Rainfall redistribution through the vegetation canopy plays a key role in the hydrological cycle. Although there have been studies on the heterogeneous patterns of rainfall redistribution in some ecosystems, the understanding of this process in different stages of forest succession remains insufficient. Therefore, this study investigated the change tendency in rainfall redistribution and rainwater chemistry in a subtropical forest succession in South China, based on 22 years (2001–2022) of rainfall monitoring (740 valid events). Results showed that, at the event scale, both the throughfall ratio and the stemflow ratio in pine forest (PF) were higher than in mixed forest (MF) and broadleaf forest (BF). At the interannual scale, throughfall and stemflow of forests experienced an initial decrease followed by a subsequent increase over the entire measurement period (except stemflow of the pine forest), which reflects the trend in open rainfall. The variability in throughfall showed an increase from MF to PF to BF, and the variability in stemflow likewise showed an increase from MF to PF to BF. Changes in throughfall and stemflow in the BF are thus higher than those in the MF and PF over time. Furthermore, important differences in rainwater chemistry fluxes among the three forest types were found, changing in varying order over time. On average, total nitrogen (TN) and total phosphorus (TP) fluxes of throughfall increased from BF to MF to PF, while the potassium (K+) flux of throughfall showed a decrease from BF to MF to PF. Stemflow chemical fluxes varied less among forest types and over time, although tree species most importantly affected varying stemflow chemistry. These results show important changes in patterns of rainfall redistribution over time and that characteristic variations are driven by rainfall and forest factors. Therefore, this study provides insight into long-term rainfall redistribution processes by linking changes in rainfall spectra with a typical subtropical forest succession sequence.

During the first half of the Holocene (11 000 to 5000 years ago), the Northern Hemisphere experienced a strengthening of the monsoonal regime, with climate reconstructions robustly suggesting a greening of the Sahara region. Palaeoclimate archives also show that this so-called African humid period (AHP) was accompanied by changes in climate conditions at middle to high latitudes. However, inconsistencies still exist in reconstructions of the mid-Holocene (MH) climate at mid-latitudes, and model simulations provide limited support in reducing these discrepancies. In this paper, a set of simulations performed using a climate model are used to investigate the hitherto unexplored impact of Saharan greening on mid-latitude atmospheric circulation during the MH. Numerical simulations show Saharan greening has a year-round impact on the main circulation features in the Northern Hemisphere, especially during boreal summer (when the African monsoon develops). Key findings include a westward shift in the global Walker Circulation, leading to modifications in the North Atlantic jet stream in summer and the North Pacific jet stream in winter. Furthermore, Saharan greening modifies atmospheric synoptic circulation over the North Atlantic, enhancing the effect of orbital forcing on the transition of the North Atlantic Oscillation phase from predominantly positive to negative in winter and summer. Although the prescription of vegetation in the Sahara does not improve the proxy–model agreement, this study provides the first constraint on the influence of Saharan greening on northern mid-latitudes, opening new opportunities for understanding MH climate anomalies in regions such as North America and Eurasia.

Biogenic volatile organic compounds (BVOCs), as a crucial component that impacts atmospheric chemistry and ecological interactions with various organisms, play a significant role in the atmosphere–ecosystem relationship. However, traditional field observation methods are challenging for accurately estimating BVOC emissions in forest ecosystems with high biodiversity, leading to significant uncertainty in quantifying these compounds. To address this issue, this research proposes a workflow utilizing drone-mounted lidar and photogrammetry technologies for identifying plant species to obtain accurate BVOC emission data. By applying this workflow to a typical subtropical forest plot, the following findings were made: the drone-mounted lidar and photogrammetry modules effectively segmented trees and acquired single wood structures and images of each tree. Image recognition technology enabled relatively accurate identification of tree species, with the highest-frequency family being Euphorbiaceae. The largest cumulative isoprene emissions in the study plot were from the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family. To fully leverage the estimation results of BVOC emissions directly from individual tree levels, it may be necessary for communities to establish more comprehensive tree species emission databases and models.

Levelling errors are defined as the data difference among flight lines in airborne geophysical data. The differences in the signal levelling always appear as a striping pattern parallel to the flight lines on the imaged maps. The fixed structured pattern inspires us to structure a guided levelling error model using an anisotropic Gabor filter. We then embed the levelling error model into a total variational framework to flexibly calculate levelling errors. The guided levelling error model constrains the noise term of total variation rather than just using blind removal. Moreover, we can also apply the structured variational method to remove other noises in airborne geophysical data. This would just require replacing the noise prior models in the proposed method. We have applied this method to the airborne electromagnetic, magnetic, and apparent conductivity data collected by the Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data. The structured variational method can better level the airborne geophysical data based on the space properties of the levelling error.

Constructing a highly resolved comprehensive emission dataset for China is challenging due to limited availability of refined information for parameters in a unified bottom-up framework. Here, by developing an integrated modeling framework, we harmonized multi-source heterogeneous data, including several up-to-date emission inventories at national and regional scales and for key species and sources in China to generate a 0.1° resolution inventory for 2017. By source mapping, species mapping, temporal disaggregation, spatial allocation, and spatial–temporal coupling, different emission inventories are normalized in terms of source categories, chemical species, and spatiotemporal resolutions. This achieves the coupling of multi-scale, high-resolution emission inventories with the Multi-resolution Emission Inventory for China (MEIC), forming the high-resolution INTegrated emission inventory of Air pollutants for China (INTAC). We find that INTAC provides more accurate representations for emission magnitudes and spatiotemporal patterns. In 2017, China's emissions of sulfur dioxide (SO2), nitrous oxides (NOx), carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs), ammonia (NH3), PM10 and PM2.5 (particulate matter), black carbon (BC), and organic carbon (OC) were 12.3, 24.5, 141.0, 27.9, 9.2, 11.1, 8.4, 1.3, and 2.2 Tg, respectively. The proportion of point source emissions for SO2, PM10, NOx, and PM2.5 increases from 7 %–19 % in MEIC to 48 %–66 % in INTAC, resulting in improved spatial accuracy, especially mitigating overestimations in densely populated areas. Compared with MEIC, INTAC reduces mean biases in simulated concentrations of major air pollutants by 2–14 µg m−3 across 74 cities, compared against ground observations. The enhanced model performance by INTAC is particularly evident at finer-grid resolutions. Our new dataset is accessible at http://meicmodel.org.cn/intac (last access: 15 April 2024) and https://doi.org/10.5281/zenodo.10459198 (Wu et al., 2024), and it will provide a solid data foundation for fine-scale atmospheric research and air-quality improvement.

Biochar (BC) application to croplands aims to sequester carbon and improve soil quality, but its impact on soil organic carbon (SOC) dynamics is not represented in most land models used for assessing land-based climate change mitigation; therefore, we are unable to quantify the effects of biochar application under different climate or land management conditions. Here, to fill this gap, we implement a submodel to represent biochar in a microbial decomposition model named MIMICS (MIcrobial-MIneral Carbon Stabilization). We first calibrate and validate MIMICS with new representations of the density-dependent microbial turnover rate, adsorption of available organic carbon on mineral soil particles, and soil moisture effects on decomposition using global field-measured cropland SOC at 285 sites. We further integrate biochar in MIMICS by accounting for its effect on microbial decomposition and SOC sorption/desorption and optimize two biochar-related parameters in these processes using 134 paired SOC measurements with and without biochar addition. The MIMICS-biochar version can generally reproduce the short-term (≤ 6 years) and long-term (8 years) SOC changes after adding (mean addition rate of 25.6 t ha−1) biochar (R2= 0.79 and 0.97, respectively) with a low root-mean-square error (RMSE = 3.73 and 6.08 g kg−1, respectively). Our study incorporates sorption and soil moisture processes into MIMICS and extends its capacity to simulate biochar decomposition, providing a useful tool to couple with dynamic land models to evaluate the effectiveness of biochar application with respect to removing CO2 from the atmosphere.

It is an important step to realize automatic and intelligent production of coal mine to use intelligent sorting robot instead of manual. The vision system, as the “eye” of the intelligent sorting robot, completes the rapid identification, positioning and grouping of the sorting target. Based on YOLOv5, the vision system uses GhostNet to carry out the lightweight design of the model, aiming to ensure the detection accuracy while making the entire model more lightweight, so as to improve the model recognition speed and reduce the operating cost. The model recognition speed of Ghost-YOLOv5 designed and developed is 33FPS, the model size is only 4,2 Mb, and the average detection accuracy is 96,7 %.

Ice microphysics controls cloud electrification in thunderstorms, and the various secondary ice production (SIP) processes are vital in generating high ice concentrations. However, the role of SIP in cold-season thunderstorms is not well understood. In this study, the impacts of SIP on the electrification in a thunderstorm that occurred in late November are investigated using model simulations. The parameterizations of four SIP processes are implemented in the model, including the rime splintering, ice–ice collisional breakup, shattering of freezing drops, and sublimational breakup of ice. In addition, a noninductive charging parameterization and an inductive charging parameterization, as well as a bulk discharging model, are coupled with the spectral bin microphysics scheme. The macroscopic characteristics and the temporal evolution of this thunderstorm are well modeled. The radar reflectivity and flash rate obtained by adding four SIP processes are more consistent with the observations than those without SIP. Among the four SIP processes, the rime splintering has the strongest impact on the storm. The graupel and snow concentrations are enhanced while their sizes are suppressed due to the SIP. The changes in the ice microphysics result in substantial changes in the charge structure. The total charge density changes from an inverted tripole structure to a dipole structure (tripole structure at some locations) after four SIP processes are considered in the model, mainly due to the enhanced collision between graupel and ice. These changes lead to an enhancement of the vertical electric field, especially in the mature stage, which explains the improved modeling of flash rate. The results highlight that cold-season cloud electrification is very sensitive to the SIP processes.

Multiple sensors equipped on the Unmanned Aerial Vehicle (UAV) enables the acquisition of multi-modal and multi-source remote sensing data. UAV remote sensing usually faces with real-time or near-real-time tasks in complex and highly dynamic environments, such as disaster monitoring, traffic management, border patrol and so on. Under these conditions, the image fusion algorithm needs to be high efficiency, precision and reliability. In this paper, we proposed an intelligent real-time fusion network for UAV multi-source remote sensing data based on AI brain-like chips, and deployed the algorithm on the UAV platform to achieve online high-efficiency computing. Firstly, we have developed a novel image fusion algorithm named SFNet for infrared and visible image fusion based on ShuffleNetv2. Then, we use ZCA and l1-norm to process the remodeled deep feature. The weight maps are generated by bi-cubic interpolation and soft-max operation. Finally, the fused image is reconstructed by weighted-average operation. The proposed SFNet is deployed on the Lynxi KA200 brain computing chip, and a comprehensive inference test is carried out with UAV remote sensing data. Several State-Of-The-Art (SOTA) data fusion algorithms are deployed on the same chip for experimental comparison. The proposed SFNet is proved to have faster inference speed and better feature extraction results on brain-like chips. It is more suitable for real-time UAV remote sensing image fusion tasks.

Moving target tracking technology based on Unmanned Aerial Vehicles (UAV) is widely used in many fields such as automatic inspection and emergency response. The existing moving target tracking methods usually have the problems of large computation and low tracking efficiency. Limited by the computing power of the UAV platform, real-time tracking and analysis of multiple targets based on the video data collected by UAV platform is a difficult task. In this paper, we proposed a novel Target Specific Filtering Tracking with Memory (TSFMTrack) method designed for UAV-based real-time tracking tasks, which involves a Tracklet Filtering Module (TFM) for capturing object appearance features and a Tracklet Matching Module (TMM) for bounding box association in each frame. By experimental comparison with other State-Of-The-Art (SOTA) methods on popular MOT and UAV tracking datasets, the TSFMTrack have shown obvious advantages in accuracy, computational efficiency and reliability. Furthermore, we deployed the TSFMTrack on the brain-inspired chip Lynchip KA200, the experimental results have shown that the TSFMTrack is effective on edge computational platform and suitable for UAV real-time tracking tasks.

Synthetic Aperture Radar (SAR) holds significant potential for applications in crop monitoring and classification. Interferometric SAR (InSAR) coherence proves effective in monitoring crop growth. Currently, the coherence based on the maximum likelihood estimator is biased towards low coherence values. Therefore, the main aim of this work is to access the performance of Sentinel-1 time-series biased coherence and unbiased coherence in crop monitoring and classification. This study was conducted during the 2018 growing season (April-October) in Komoka, an agricultural region in southwestern Ontario, Canada, primarily cultivating three crops: soybean, corn, and winter wheat. To verify the ability of coherence to monitor crops, a linear correlation coefficient between temporal coherence and dual polarimetric radar vegetation index (DpRVI) was fitted. The results revealed a stable correlation between temporal coherence and DpRVI time-series, with the highest correlation observed for soybean (0.7 < R < 0.8), followed by wheat and corn. Notably, unbiased coherence of the VV channel exhibited the highest correlation (R > 0.75). In addition, we applied unbiased coherence to crop classification. The results show that unbiased coherence exhibits very promising classification performance, with the overall accuracy (84.83%) and kappa coefficient (0.76) of VV improved by 8.35% and 0.12, respectively, over biased coherence, and the overall accuracy (73.25%) and kappa coefficient (0.57) of VH improved by 7.56% and 0.14, respectively, over biased coherence, and all crop classification accuracies were also effectively improved. This study demonstrates the feasibility of coherence monitoring of crops and provides new insights in enhancing the higher separability of crops.

The interactions between the terrestrial biosphere, atmospheric chemistry, and climate involve complex feedbacks that have traditionally been modeled separately. We present a new framework that couples the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic plant-chemistry model, with the RegCM-Chem model. RegCM-Chem–YIBs integrates meteorological variables and atmospheric chemical composition from RegCM-Chem with land surface parameters from YIBs. The terrestrial carbon flux calculated by YIBs is fed back into RegCM-Chem interactively, thereby representing the interactions between fine particulate matter (PM2.5), ozone (O3), and carbon dioxide (CO2). For testing purposes, we carry out a 1-year simulation (2016) at a 30 km horizontal resolution over East Asia with RegCM-Chem–YIBs. The model accurately captures the spatio-temporal distribution of climate, chemical composition, and ecological parameters. In particular, the estimated O3 and PM2.5 are consistent with ground observations, with correlation coefficients (R) of 0.74 and 0.65, respectively. The simulated CO2 concentration is consistent with observations from six sites (R ranged from 0.89 to 0.97) and exhibits a similar spatial pattern when compared with carbon assimilation products. RegCM-Chem–YIBs produces reasonably good gross primary productivity (GPP) and net primary productivity (NPP), showing seasonal and spatial distributions consistent with satellite observations, and mean biases (MBs) of 0.13 and 0.05 kg C m−2 yr−1. This study illustrates that RegCM-Chem–YIBs is a valuable tool to investigate coupled interactions between the terrestrial carbon cycle, atmospheric chemistry, and climate change at a higher resolution on a regional scale.

The scattered seismic waves of fractured porous rock are strongly affected by the wave-induced fluid pressure diffusion effects between the compliant fractures and the stiffer embedding background. To include these poroelastic effects in seismic modeling, we develop a numerical scheme for discretely distributed large-scale fractures embedded in fluid-saturated porous rock. Using Coates and Schoenberg's local-effective-medium theory and Barbosa's dynamic linear slip model characterized by complex-valued and frequency-dependent fracture compliances, we derive the effective viscoelastic compliances in each spatial discretized cell by superimposing the compliances of the background and the fractures. The effective governing equations for fractured porous rocks are viscoelastic anisotropic and numerically solved by the mixed-grid-stencil frequency-domain finite-difference method. The main advantage of our proposed modeling scheme over poroelastic modeling schemes is that the fractured domain can be modeled using a viscoelastic solid, while the rest of the domain can be modeled using an elastic solid. We have tested the modeling scheme in a single fracture model, a fractured model, and a modified Marmousi model. The good consistency between the scattered waves off a single horizontal fracture calculated using our proposed scheme and the poroelastic modeling validates that our modeling scheme can properly capture the fluid pressure diffusion (FPD) effects. In the case of a set of aligned fractures, the scattered waves from the top and bottom of the fractured reservoir are strongly influenced by the FPD effects, and the reflected waves from the underlying formation can retain the relevant attenuation and dispersion information. The proposed numerical modeling scheme can also be used to improve migration quality and the estimation of fracture mechanical characteristics in inversion.

Atmospheric aerosol in the Tibetan Plateau (TP) and its surroundings has attracted significant scientific interest in recent decades due to its notable impacts on regional climatic and cryospheric changes, ecological and environmental security, and the hydrological cycle. However, our understanding of the atmospheric aerosol in this remote region is highly limited by the scarcity of available datasets owing to the extremely harsh natural conditions. This challenge has been mitigated in recent decades by establishing field observatories at typical sites within the TP and its surroundings. A continuous project initiated in 2015 aims to explore the properties and sources of atmospheric aerosols, as well as their regional differences, through multiple short-term intensive observations obtained across this vast region utilizing a suite of high-time-resolution online instruments. This paper presents a systematic and hourly scale dataset of aerosol physicochemical and optical properties at eight sites across the TP and its surroundings that is derived from the project. It includes size-resolved chemical compositions of submicron aerosols, high-resolution mass spectra and sources of organic aerosols, size distributions of particle number concentrations, particle light-scattering and light-absorption coefficients, particle light absorptions attributed to different carbonaceous substances including black carbon and brown carbon, and number concentrations of cloud condensation nuclei. In brief, atmospheric aerosols in these remote sites were all well mixed and highly aged, reflecting their dominant regional transport sources. However, the southern TP region exhibited high contributions of carbonaceous organic aerosols, neutralized bulk submicron aerosols, and a relatively high light-absorption capacity, whereas in the northern TP region, secondary inorganic species were the main contributors to the overall acidic submicron aerosols. Beyond providing insights into the regional differences in aerosol sources and properties across the TP and its surroundings, the datasets will also benefit simulations of aerosol radiative forcing and evaluations of interactions among different Earth system components in numerical models for this region. The datasets are accessible through the National Cryosphere Desert Data Center, Chinese Academy of Sciences (https://doi.org/10.12072/ncdc.NIEER.db2200.2022; Xu, 2022).

Narrowing surface ozone disparities between urban and nonurban areas escalate health risks in densely populated urban zones. A comprehensive understanding of the impact of ozone photochemistry on this transition remains constrained by current knowledge of aerosol effects and the availability of surface monitoring. Here we reconstructed spatiotemporal gapless air quality concentrations using a novel transformer deep learning (DL) framework capable of perceiving spatiotemporal dynamics to analyze ozone urban–nonurban differences. Subsequently, the photochemical effect on these discrepancies was analyzed by elucidating shifts in ozone regimes inferred from an interpretable machine learning method. The evaluations of the model exhibited an average out-of-sample cross-validation coefficient of determination of 0.96, 0.92, and 0.95 for ozone, nitrogen dioxide, and fine particulate matter (PM2.5), respectively. The ozone sensitivity in nonurban areas, dominated by a nitrogen-oxide-limited (NOx-limited) regime, was observed to shift towards increased sensitivity to volatile organic compounds (VOCs) when extended to urban areas. A third “aerosol-inhibited” regime was identified in the Jiaodong Peninsula, where the uptake of hydroperoxyl radicals onto aerosols suppressed ozone production under low NOx levels during summertime. The reduction of PM2.5 could increase the sensitivity of ozone to VOCs, necessitating more stringent VOC emission abatement for urban ozone mitigation. In 2020, urban ozone levels in Shandong surpassed those in nonurban areas, primarily due to a more pronounced decrease in the latter resulting from stronger aerosol suppression effects and less reduction in PM2.5. This case study demonstrates the critical need for advanced spatially resolved models and interpretable analysis in tackling ozone pollution challenges.

The MIXv2 Asian emission inventory is developed under the framework of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase IV and produced from a mosaic of up-to-date regional emission inventories. We estimated the emissions for anthropogenic and biomass burning sources covering 23 countries and regions in East, Southeast and South Asia and aggregated emissions to a uniform spatial and temporal resolution for seven sectors: power, industry, residential, transportation, agriculture, open biomass burning and shipping. Compared to MIXv1, we extended the dataset to 2010–2017, included emissions of open biomass burning and shipping, and provided model-ready emissions of SAPRC99, SAPRC07, and CB05. A series of unit-based point source information was incorporated covering power plants in China and India. A consistent speciation framework for non-methane volatile organic compounds (NMVOCs) was applied to develop emissions by three chemical mechanisms. The total Asian emissions for anthropogenic/open biomass sectors in 2017 are estimated as follows: 41.6/1.1 Tg NOx, 33.2/0.1 Tg SO2, 258.2/20.6 Tg CO, 61.8/8.2 Tg NMVOC, 28.3/0.3 Tg NH3, 24.0/2.6 Tg PM10, 16.7/2.0 Tg PM2.5, 2.7/0.1 Tg BC (black carbon), 5.3/0.9 Tg OC (organic carbon), and 18.0/0.4 Pg CO2. The contributions of India and Southeast Asia were emerging in Asia during 2010–2017, especially for SO2, NH3 and particulate matter. Gridded emissions at a spatial resolution of 0.1° with monthly variations are now publicly available. This updated long-term emission mosaic inventory is ready to facilitate air quality and climate model simulations, as well as policymaking and associated analyses.

A high-resolution soot particle aerosol mass spectrometer (SP-AMS) was used to selectively measure refractory black carbon (rBC) and its associated coating material using both the ensemble size-resolved mass spectral mode and the event trigger single particle (ETSP) mode in Houston, Texas, in summer 2022. This study was conducted as part of the Department of Energy Atmospheric Radiation Measurement (ARM) program's TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign. The study revealed an average (±1σ) rBC concentration of 103 ± 176 ng m−3. Additionally, the coatings on the BC particles were primarily composed of organics (59 %; 219 ± 260 ng m−3) and sulfate (26 %; 94 ± 55 ng m−3). Positive matrix factorization (PMF) analysis of the ensemble mass spectra of BC-containing particles resolved four distinct types of soot aerosol, including an oxidized organic aerosol (OOABC,PMF) factor associated with processed primary organic aerosol, an inorganic sulfate factor (SO4,BC,PMF), an oxidized rBC factor (O-BCPMF), and a mixed mineral dust–biomass burning aerosol factor with significant contribution from potassium (K-BBBC,PMF). Additionally, K-means clustering analysis of the single-particle mass spectra identified eight different clusters, including soot particles enriched in hydrocarbon-like organic aerosol (HOABC,ETSP), sulfate (SO4,BC,ETSP), two types of rBC, OOA (OOABC,ETSP), chloride (ClBC,ETSP), and nitrate (NO3,BC,ETSP). The single-particle measurements demonstrate substantial variation in BC coating thickness with coating-to-rBC mass ratios ranging from 0.1 to 100. The mixing state index (χ), which denotes the degree of homogeneity of the soot aerosol, varied from 4 % to 94 % with a median of 40 %, indicating that the aerosol population lies in between internal and external mixing but has large temporal and source type variability. In addition, a significant fraction of BC-containing particles, a majority enriched with oxidized organics and sulfate, exhibit sufficiently high κ values and diameters conducive to activation as cloud nuclei under atmospherically relevant supersaturation conditions. This finding bears significance in comprehending the aging processes of rBC-containing particles and their activation into cloud droplets. Our analysis highlights the complex nature of soot aerosol and underscores the need to comprehend its variability across different environments for accurate assessment of climate change.

Particulate matter has major climate and health impacts, and it is therefore of utmost importance to be able to measure the composition of these particles to gain insights into their sources and characteristics. Many methods, both offline and online, have been employed over the years to achieve this goal. One of the most recent developments is the Vaporization Inlet for Aerosols (VIA) coupled to a nitrate Chemical Ionization Mass Spectrometer (NO3-CIMS), but a thorough understanding of the VIA–NO3-CIMS system remains incomplete. In this work, we ran a series of tests to assess the impacts from different systems and sampling parameters on the detection efficiency of highly oxygenated organic molecules (HOMs) in the VIA–NO3-CIMS system. Firstly, we found that the current VIA system (which includes an activated carbon denuder and a vaporization tube) efficiently transmits particles (> 90 % for particles larger than 50 nm) while also removing gaseous compounds (> 97% for tested volatile organic compounds – VOCs). One of the main differences between the VIA and traditional thermal desorption (TD) techniques is the very short residence time in the heating region, on the order of 0.1 s. We found that this short residence time, and the corresponding short contact with heated surfaces, is likely one of the main reasons why relatively reactive or weakly bound peroxides, for example, were observable using the VIA. However, the VIA also requires much higher temperatures in order to fully evaporate the aerosol components. For example, the evaporation temperature of ammonium sulfate particles using the VIA was found to be about 100–150 °C higher than in typical TD systems. We also observed that the evaporation of particles with larger sizes occurred at slightly higher temperatures compared to smaller particles. Another major aspect that we investigated was the gas-phase wall losses of evaporated molecules. With a more optimized interface between the VIA and the NO3-CIMS, we were able to greatly decrease wall losses and thus improve the sensitivity compared to our earlier VIA work. This interface included a dedicated sheath flow unit to cool the heated sample and provide the NO3-CIMS with the needed high flow (10 L min−1). Our results indicate that most organic molecules observable by the NO3-CIMS can evaporate and be transported efficiently in the VIA system, but upon contact with the hot walls of the VIA, the molecules are instantaneously lost. This loss potentially leads to fragmentation products that are not observable by the NO3-CIMS. Thermograms, obtained by scanning the VIA temperature, were found to be very valuable for both quantification purposes and for estimating the volatility of the evaporating compounds. We developed a simple one-dimensional model to account for the evaporation of particles and the temperature-dependent wall losses of the evaporated molecules, and we thereby estimate the concentration of HOMs in secondary organic aerosol (SOA) particles. Overall, our results provide much-needed insights into the key processes underlying the VIA–NO3-CIMS method. Although there are still some limitations that could be addressed through hardware improvements, the VIA–NO3-CIMS system is a very promising and useful system for fast online measurements of HOMs in the particle phase.

In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and its main precursor NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local-emission-dominant case but led to the model O3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea.

Three-dimensional (3D) printers have become popular educational tools in secondary and post-secondary STEM curriculum; however, concerns have emerged regarding inhalation exposures and associated health risks. Current evidence suggests that filament materials and site conditions may cause differences in the chemical profiles and toxicological properties of 3D printer emissions; however, few studies have evaluated exposures directly in the classroom. In this study, we monitored and sampled particulate matter (PM) emitted from acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA) filaments during a 3-hour 3D printing session in a high school classroom using aerosol monitoring instrumentation and collection media. To evaluate potential inhalation risks, Multiple Path Particle Dosimetry (MPPD) modeling was used to estimate inhaled doses and calculate in vitro concentrations based on the observed aerosol data and specific lung and breathing characteristics. Dynamic light scattering was used to evaluate the hydrodynamic diameter, zeta potential, and polydispersity index (PDI) of extracted PM emissions dispersed in cell culture media. Small airway epithelial cells (SAEC) were employed to determine cellular viability, genotoxic, inflammatory, and metabolic responses to each emission exposure using MTS, ELISA, and high-performance liquid chromatography-mass spectrometry (HPLC-MS), respectively. Aerosol monitoring data revealed that emissions from ABS and PLA filaments generated similar PM concentrations within the ultrafine and fine ranges. However, DLS analysis showed differences in the physicochemical properties of ABS and PLA PM, where the hydrodynamic diameter of PLA PM was greater than ABS PM, which may have influenced particle deposition rates and cellular outcomes. While exposure to both ABS and PLA PM reduced cell viability and induced MDM2, an indicator of genomic instability, PLA PM alone increased gamma-H2AX, a marker of double-stranded DNA breaks. ABS and PLA emissions also increased the release of pro-inflammatory cytokines, although this did not reach significance. Furthermore, metabolic profiling via high performance liquid chromatography-mass spectrometry (HPLC-MS) and subsequent pathway analysis revealed filament and dose dependent cellular metabolic alterations. Notably, our metabolomic analysis also revealed key metabolites and pathways implicated in PM-induced oxidative stress, DNA damage, and respiratory disease that were perturbed across both tested doses for a given filament. Taken together, these findings suggest that use of ABS and PLA filaments in 3D printers within school settings may potentially contribute to adverse respiratory responses especially in vulnerable populations.

The seasonal dynamic of the suprapermafrost groundwater significantly affects the runoff generation and confluence in permafrost basins and is a leading issue that must urgently be addressed in hydrological research in cold and alpine regions. In this study, the seasonal dynamic process of the suprapermafrost groundwater level (SGL), vertical gradient changes of soil temperature (ST), moisture content in the active layer (AL), and river level changes were analyzed at four permafrost watersheds in the Qinghai–Tibet Plateau using comparative analysis and the nonlinear correlation evaluation method. The impact of freeze–thaw processes on seasonal SGL and the links between SGL and surface runoff were also investigated. The SGL process in a hydrological year can be divided into four periods: (A) a rapid falling period (October to mid-November), (B) a stable low-water period (late November to May), (C) a rapid rising period (approximately June), and (D) a stable high-water period (July to September), which synchronously respond to seasonal variations in soil moisture and temperature in the AL. The characteristics and causes of SGL changes significantly varied during these four periods. The freeze–thaw process of the AL regulated SGL and surface runoff in permafrost watersheds. During period A, with rapid AL freezing, the ST had a dominant impact on the SGL. In period B, the AL was entirely frozen due to the stably low ST, while the SGL dropped to the lowest level with small changes. During period C, ST in the deep soil layers of AL (below 50 cm depth) significantly impacted the SGL (nonlinear correlation coefficient R2 > 0.74, P < 0.05), whereas the SGL change in the shallow soil layer (0–50 cm depth) showed a closer association with soil moisture content. Rainfall was the major cause for the stable high SGL during period D. In addition, the SGLs in periods C and D were closely linked to the retreat and flood processes of river runoff. The SGL contributed approximately 57.0 %–65.8 % of the river runoff changes in the period D. These findings will help to facilitate future hydrological research in the permafrost basins and the development and utilization of water resources in cold and alpine regions.