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The warming radiative forcing effect (RFE) derived from atmospheric amines attracts a lot of attention because of their contribution to brown carbon. Herein, the enhanced influence of amines (methyl-, dimethyl-, and trimethylamine) on cooling RFE of mineral particles is first confirmed at visible wavelengths. Present results state heterogeneous uptake and oxidation reactions of atmospheric amines are feasible on mineral particles under clean and polluted conditions, which are proven by related thermodynamics and kinetics data obtained using combined classical molecular dynamics and density function theory methods. Based on mineral particles, simple forcing efficiency (SFE) results explain that amine uptake induces at least 11.8 %–29.5 % enhancement on cooling RFE of amine–mineral particles at visible wavelengths. After amine heterogeneous oxidation, oxidized amine–mineral particle cooling RFEs are furthermore enhanced due to increased oxygen contents. Moreover, oxidized amine–mineral particles under clean conditions show 27.1 %–47.1 % SFE increments at 400–600 nm, which is at least 11.3 % higher than that of itself under polluted conditions, due to high-oxygen-content product formation through amine autoxidation. Our results suggest cooling RFE derived from atmospheric amines can be equally important to their warming RFE on the atmosphere. It is necessary to update the heterogeneous oxidation mechanism and kinetics data of amines in atmospheric models in order to accurately evaluate the whole RFE caused by amines on the atmosphere.

Persistent winter aerosol pollution frequently occurs in the Sichuan Basin (SCB) due to its unfavourable weather conditions, such as low wind, wetness, and cloudiness. Based on long-term observational data analyses from 2015–2021, it has been found that the four representative stations in the SCB often simultaneously experience PM2.5 pollution accompanied by variations in meteorological conditions above 850 hPa, which indicates a connection between regional winter air pollution in the SCB and large-scale synoptic patterns. The dominant 850 hPa synoptic patterns of winter in the SCB were classified into six patterns using T-model principal component analysis: (1) strong high pressure in the north, (2) east high–west low (EHWL) pressure, (3) weak high pressure in the north, (4) a weak ridge of high pressure after the trough, (5) a low trough (LT), and (6) strong high pressure. Pattern 2 characterized by the EHWL pressure system, and Pattern 5, featured with LT, was identified as having key synoptic patterns for the beginning and accumulation of pollution processes. Pattern 1, characterized by a strong high pressure in the north, was the cleanest pattern associated with reduced PM2.5 concentrations. The EHWL and LT patterns were associated with a remarkably high cloud liquid content attributed to upper southerly winds introducing humid air. Clouds reduce solar radiation through reflection and scattering, resulting in more stable stratification and aerosol accumulation. This cloud radiation interaction (CRI) was more pronounced in the LT pattern due to denser isobaric lines and stronger southerly winds than in the EHWL pattern. Numerical simulation experiments utilizing WRF-Chem indicated that there is an upper-level heating during afternoon and surface cooling in the morning forced by the aerosol radiation interaction (ARI) under the EHWL and LT patterns. Additionally, strong surface cooling in the evening influenced by valley winds could be found. With wet and cloudy synoptic forcing, ARI directly affects the stability of the boundary layer and is modulated through CRI inhibition. For example, Chongqing exhibited lower PM2.5 concentrations and stronger ARI compared to the western and southern SCB due to lower cloud liquid content and weaker CRI inhibition on the ARI. The CRI inhibition caused a 50 % reduction in solar radiation and boundary layer height during the daytime under the LT pattern, which was larger than that under the EHWL pattern. This study comprehensively analysed the spatial disparities in cloud inhibition on the ARIs, their impacts on the boundary layer structure, and the discrepancies of these interactions under different synoptic patterns during pollution processes. The findings have important implications for the effective management of pollution processes in cloudy and foggy weather.

We present direct measurements of biogenic volatile organic compound (BVOC)-induced nitrate radical (NO3) reactivity (kVOC) through the diel cycle in the suburban, temperate forest of Rambouillet near Paris (France). The data were obtained in a 6-week summer period in 2022 as part of the Atmospheric ChemistRy Of the Suburban foreSt (ACROSS) campaign. kVOC was measured in a small (700 m2) clearing mainly at a height of 5.5 m above ground level but also at 40 m (for 5 d and nights). At nighttime, mean values (and 25th–75th percentile ranges) of knightVOC(5.5m) = (0.24-0.06+0.32) s−1 and knightVOC(40m) = (0.016-0.007+0.018) s−1 indicate a significant vertical gradient and low NO3 reactivity above the canopy, whereas knightVOC(5.5 m) showed peak values of up to 2 s−1 close to the ground. The strong vertical gradient in NO3 reactivity could be confirmed by measurements between 0 and 24 m on one particular night characterized by a strong temperature inversion and is a result of the decoupling of air masses aloft from the ground- and canopy-level sources of BVOCs (and nitric oxide, NO). No strong vertical gradient was observed in the mean daytime NO3 reactivity, with kdayVOC(5.5m) = (0.12 ± 0.04) s−1 for the entire campaign and kdayVOC(40m) = (0.07 ± 0.02) s−1 during the 5 d period. Within the clearing, the fractional contribution of VOCs to the total NO3 loss rate coefficient (ktot, determined by photolysis, reaction with NO and VOCs) was 80 %–90 % during the night and ∼ 50 % during the day. In terms of chemical losses of α-pinene below canopy height in the clearing, we find that at nighttime hydroxyl radicals (OH) and ozone (O3) dominate, with NO3 contributing “only” 17 %, which decreases further to 8.5 % during the day. Based on measured OH, measured O3, and calculated NO3 concentrations, the chemical lifetime of BVOCs at noon is about 1 h and is likely to be longer than timescales of transport out of the canopy (typically of the order of minutes), thus significantly reducing the importance of daytime in-canopy processing. Clearly, in forested regions where sufficient nitric oxide and nitrogen dioxide (NOx) is available, the role of NO3 and OH as initiators of BVOC oxidation is not strictly limited to nighttime and daytime, respectively, as often implied in e.g. atmospheric chemistry textbooks.

Mandatory use of low-sulfur fuel according to the global sulfur limit regulation has reduced the emissions of SO2 and particulate matter (PM) significantly on ships, and it also leads to a very large uncertainty in volatile organic compound (VOC) emissions. Therefore, an on-board test of VOCs from nine typical cargo ships with low-sulfur fuels in China was carried out in this study. Results showed that the emission factor of VOCs (EFVOCs) varied largely from 0.09 to 3.01 g kg−1 of fuel, with domestic coastal cargo ships (CCSs) having the highest level, followed by inland cargo ships (ICSs) and ocean-going vessels (OGVs). The switch of fuels from heavy fuel oil (HFO) to diesel increased EFVOCs by 48 % on average, which enhanced both O3 and secondary organic aerosol (SOA) formation potential, especially for OGVs. Besides, the use of low-sulfur fuels for OGVs also led to a significant increase in naphthalene emission. These indicated that the implementation of a global ultra-low-sulfur oil policy in the near future needs to be optimized. Moreover, aromatics were the most important common contributors to O3 and SOA in ship exhausts, which need to be controlled as a matter of priority. It was also found that the benzene, toluene, and ethylbenzene ratio of 0.5:0.3:0.2 on average could be considered a diagnostic characteristic to distinguish ship emissions from other emission sources.

Abstract Exploring the mysterious dark matter is a key quest in modern physics. Currently, detecting axions, a hypothetical particle proposed as a primary component of dark matter, remains a significant challenge due to their weakly interacting nature. Here we show at quantum level that in a cavity permeated by a magnetic field, the single axion-photon conversion rate is enhanced by the cavity quality factor and is quantitatively larger than the classical result by π/2. The axion cavity can be considered a quantum device emitting single photons with temporal separations. This differs from the classical picture and reveals a possibility for the axion cavity experiment to handle the signal sensitivity at the quantum level, e.g., a dual path quantum interferometry with cross-power and second-order correlation measurements. This scheme would greatly reduce the signal scanning time and improve the sensitivity of the axion-photon coupling, potentially leading to the direct observation of axions.

Abstract Dissipative Kerr soliton microcombs in microresonators have enabled fundamental advances in chip-scale precision metrology, communication, spectroscopy, and parallel signal processing. Here we demonstrate polarization-diverse soliton transitions and deterministic switching dynamics of a self-stabilized microcomb in a strongly-coupled dispersion-managed microresonator driven with a single pump laser. The switching dynamics are induced by the differential thermorefractivity between coupled transverse-magnetic and transverse-electric supermodes during the forward-backward pump detunings. The achieved large soliton existence range and deterministic transitions benefit from the switching dynamics, leading to the cross-polarized soliton microcomb formation when driven in the transverse-magnetic supermode of the single resonator. Secondly, we demonstrate two distinct polarization-diverse soliton formation routes – arising from chaotic or periodically-modulated waveforms via pump power selection. Thirdly, to observe the cross-polarized supermode transition dynamics, we develop a parametric temporal magnifier with picosecond resolution, MHz frame rate and sub-ns temporal windows. We construct picosecond temporal transition portraits in 100-ns recording length of the strongly-coupled solitons, mapping the transitions from multiple soliton molecular states to singlet solitons. This study underpins polarization-diverse soliton microcombs for chip-scale ultrashort pulse generation, supporting applications in frequency and precision metrology, communications, spectroscopy and information processing.

Abstract Quantum Boltzmann machines (QBMs) are machine-learning models for both classical and quantum data. We give an operational definition of QBM learning in terms of the difference in expectation values between the model and target, taking into account the polynomial size of the data set. By using the relative entropy as a loss function, this problem can be solved without encountering barren plateaus. We prove that a solution can be obtained with stochastic gradient descent using at most a polynomial number of Gibbs states. We also prove that pre-training on a subset of the QBM parameters can only lower the sample complexity bounds. In particular, we give pre-training strategies based on mean-field, Gaussian Fermionic, and geometrically local Hamiltonians. We verify these models and our theoretical findings numerically on a quantum and a classical data set. Our results establish that QBMs are promising machine learning models.

Abstract Li4Ti5O12 (LTO) is known for its zero-strain characteristic in electrochemical applications, making it a suitable material for fast-charging applications. Here, we systematically studied the quasi-equilibrium and non-equilibrium lithium-ion transportation kinetics in LTO thin-film electrodes, across a range of scales from the crystal lattice to the microstructured electrodes. At the crystal lattice scale, during the non-equilibrium lithiation process, lithium ions are dispersedly embedded into the 16c position, resulting in more 8a → 16c migration compared with the quasi-equilibrium lithiation, and forming numerous fast lithium diffusion channels inside the LTO lattice. At the microstructural electrode scale, optical spectrum characterizations supported the “nano-filaments” lithiation model in polycrystalline LTO thin-film electrodes during the lithiation process. Our results reveal the patterns of lithium migration and distribution within the LTO thin film electrode under the non-equilibrium and quasi-equilibrium lithiation process, offering profound insights into the potential optimization strategies for enhancing the performance of fast-charging thin film batteries.

Abstract Exploiting the utility of near-term quantum devices is a long-standing challenge whereas hybrid quantum machine learning emerges as a promising candidate. Here we propose a quantum-enhanced deep generative algorithm based on programmable quantum circuit-induced quantum latent codes. To validate the effectiveness of the algorithm, we conduct optical ghost imaging experiments, collecting dataset under varying physical sampling rates. Leveraging a physically enhanced loss function and a pretrained neural network, the quantum algorithm exhibits superior reconstruction performance compared to conventional algorithms. We observe the learnable quantum latent space enhances the out-of-distribution generalization capability of the pretrained model. In the context of computer vision problems, numerical results indicate that quantum latent space can increase the generation diversity of the pretrained model. Furthermore, the algorithm outperforms classical counterparts, particularly in image inpainting and colorization, by a significant margin. Our study demonstrates the utility of hybrid quantum-classical algorithms in enhancing generalization capability, highlighting the potential of near-term quantum devices in large-scale generative artificial intelligence.

Abstract Two-dimensional topological semimetals are typically characterized by the vorticity of gapless points, and can be classified according to the band representations. However, the topological properties involving the distribution of the Berry curvature in the entire Brillouin zone are often overlooked. In this study, we investigate a two-band two-dimensional topological semimetal protected by C 4z T magnetic symmetry, exhibiting a two-fold band degeneracy at the Γ(0, 0) and M(π, π) points. Due to the presence of C 4z T symmetry, the Brillouin zone is divided into two patches characterized by half-quantized Berry curvature fluxes with opposite signs. In multi-band case, the half-quantization deviates, indicating the fragile nature. The semimetal presents counter-propagating half-edge channels, accompanied by power-law decaying and oscillating edge currents. The band topology leads to unconventional Landau levels featuring anisotropic edge modes. Each massless Dirac cone, associated with the half-quantized Berry curvature flux, exhibits an integer quantum Hall conductance. Additionally, we calculate the local orbital magnetization with open boundary conditions in both the x and y directions. This reveals isolated magnetization islands, highlighting an experimentally observable magnetic phenomenon in this topological semimetal.

Abstract UTe2 is a promising candidate for spin-triplet superconductors, in which a paramagnetic normal state becomes superconducting due to spin fluctuations. Here, we theoretically show that electron correlation induces a dramatic change in the normal state fermiology with an emergent correlated Fermi surface (FS) driven by Kondo resonance at low temperatures. This emergent correlated FS can account for various unconventional superconducting properties in a unified way. In particular, the geometry of the correlated FS can naturally host topological superconductivity in the presence of odd-parity pairings, which become the leading instability due to strong ferromagnetic spin fluctuations. Moreover, two pairs of odd-parity channels appear as nearly degenerate solutions which may lead to time-reversal breaking multicomponent superconductivity. The resulting time-reversal-breaking superconducting state is a Weyl superconductor in which Weyl points migrate along the correlated FS as the relative magnitude of nearly degenerate pairing solutions varies.

Abstract Attribute to their robustness against loss and external noise, nonreciprocal photonic devices hold great promise for applications in quantum information processing. Recent advancements have demonstrated that nonreciprocal optical transmission in linear systems can be achieved through the strategic introduction of loss. However, a crucial question remains unanswered: can loss be harnessed as a resource for generating nonreciprocal quantum correlations? Here, we take a counterintuitive stance by engineering loss to generate a vital form of nonreciprocal quantum correlations, termed nonreciprocal photon blockade. We examine a dissipative three-cavity system comprising two nonlinear cavities and a linear cavity. The interplay of loss and nonlinearity leads to a robust nonreciprocal single- and two-photon blockade, facilitated by destructive quantum interference. Furthermore, we demonstrate the tunability of this nonreciprocal photon blockade by manipulating the relative phase between the two nonlinear cavities. Remarkably, this allows for the reversal of the direction of nonreciprocity. Our study not only sheds a light on the concept of loss-engineered quantum nonreciprocity but also opens up a pathway for the design of quantum nonreciprocal photonic devices.

Abstract Engineered spin-electric coupling enables spin qubits in semiconductor nanostructures to be manipulated efficiently and addressed individually. While synthetic spin-orbit coupling using a micromagnet is widely investigated for driving and entangling qubits based on single spins in silicon, the baseband control of encoded spin qubits with a micromagnet in isotopically purified silicon has been less well investigated. Here, we demonstrate fast singlet-triplet qubit oscillation (~100 MHz) in a gate-defined double quantum dot in 28Si/SiGe with an on-chip micromagnet with which we show the oscillation quality factor of an encoded spin qubit exceeding 580. The coherence time T 2* is analyzed as a function of potential detuning and an external magnetic field. In weak magnetic fields, the coherence is limited by frequency-independent noise whose time scale is faster than the typical data acquisition time of ~100 ms, which limits the T 2* below 1 μs in the ergodic limit. We present evidence of sizable and coherent coupling of the qubit with the spin states of a nearby quantum dot, demonstrating that appropriate spin-electric coupling may enable a charge-based two-qubit gate in a (1,1) charge configuration.

Abstract We demonstrate aluminum-on-silicon planar transmon qubits with time-averaged T 1 energy relaxation times of up to 270 μs, corresponding to Q = 5 million, and a highest observed value of 501 μs. Through materials analysis techniques and numerical simulations we investigate the dominant source of energy loss, and devise and demonstrate a strategy toward its mitigation. Growing aluminum films thicker than 300 nm reduces the presence of oxide, a known host of defects, near the substrate-metal interface, as confirmed by time-of-flight secondary ion mass spectrometry. A loss analysis of coplanar waveguide resonators shows that this results in a reduction of dielectric loss due to two-level system defects. The correlation between the enhanced performance of our devices and the film thickness is due to the aluminum growth in columnar structures of parallel grain boundaries: transmission electron microscopy shows larger grains in the thicker film, and consequently fewer grain boundaries containing oxide near the substrate-metal interface.

Abstract The electron pair approximation offers an efficient variational quantum eigensolver (VQE) approach for chemistry simulations on quantum computers. With the number of entangling gates scaling quadratically with system size and a constant measurement overhead, the orbital optimized unitary pair coupled cluster double (oo-upCCD) ansatz strikes a balance between accuracy and efficiency. However, the electron pair approximation prevents the method from achieving quantitative accuracy. To improve it, we explore the theory of second order perturbation (PT2) correction to oo-upCCD. PT2 accounts for the missing broken-pair contributions in oo-upCCD, while retaining its efficiencies. For molecular bond stretching and chemical reactions, the method significantly improves the predicted energy accuracy, reducing oo-upCCD’s error by up to 90%. On IonQ’s quantum computers, we find that the PT2 energy correction is highly noise-resilient. The predicted VQE-PT2 reaction energies are in excellent agreement with noise-free simulators after applying simple error mitigations solely on the VQE energies.

Abstract The immunosuppressive tumor microenvironment (TME) has become a major challenge in cancer immunotherapy, with abundant tumor-associated macrophages (TAMs) playing a key role in promoting tumor immune escape by displaying an immunosuppressive (M2) phenotype. Recently, it was reported that M1 macrophage-derived nanovesicles (M1NVs) can reprogram TAMs to an anti-tumor M1 phenotype, thereby significantly alleviating the immunosuppressive TME and enhancing the anti-tumor efficacy of immunotherapy. Herein, we developed M1NVs loaded with mesoporous dopamine (MPDA) and indocyanine green (ICG), which facilitated the recruitment of M2 TAMs through synergistic photothermal and photodynamic therapy. Thereafter, M1NVs can induce M1 repolarization of TAMs, resulting in increased infiltration of cytotoxic T lymphocytes within the tumor to promote tumor regression. This study investigated the effect of phototherapy on the immune environment of liver cancer using single-cell RNA sequencing (scRNA-seq) by comparing HCC tissues before and after MPDA/ICG@M1NVs + NIR treatment. The results showed significant shifts in cell composition and gene expression, with decreases in epithelial cells, B cells, and macrophages and increases in neutrophils and myeloid cells. Additionally, gene analysis indicated a reduction in pro-inflammatory signals and immunosuppressive functions, along with enhanced B-cell function and anti-tumor immunity, downregulation of the Gtsf1 gene in the epithelial cells of the MPDA/ICG @M1NVs + NIR group, and decreased expression of the lars2 gene in immune subpopulations. Eno3 expression is reduced in M1 macrophages, whereas Clec4a3 expression is downregulated in M2 macrophages. Notably, the B cell population decreased, whereas Pou2f2 expression increased. These genes regulate cell growth, death, metabolism, and tumor environment, indicating their key role in HCC progression. This study highlights the potential for understanding cellular and molecular dynamics to improve immunotherapy. Graphical Abstract

Abstract Surface-enhanced Raman scattering (SERS) remains a significant area of research since it’s discovery 50 years ago. The surface-based technique has been used in a wide variety of fields, most prominently in chemical detection, cellular imaging and medical diagnostics, offering high sensitivity and specificity when probing and quantifying a chosen analyte or monitoring nanoparticle uptake and accumulation. However, despite its promise, SERS is mostly confined to academic laboratories and is not recognised as a gold standard analytical technique. This is due to the variations that are observed in SERS measurements, mainly caused by poorly characterised SERS substrates, lack of universal calibration methods and uncorrelated results. To convince the wider scientific community that SERS should be a routinely used analytical technique, the field is now focusing on methods that will increase the reproducibility of the SERS signals and how to validate the results with more well-established techniques. This review explores the difficulties experienced by SERS users, the methods adopted to reduce variation and suggestions of best practices and strategies that should be adopted if one is to achieve absolute quantification. Graphical Abstract

Abstract The mass production of high-quality graphene is required for industrial application as a future electronic material. However, the chemical vapor deposition (CVD) systems previously studied for graphene production face bottlenecks in terms of quality, speed, and reproducibility. Herein, we report a novel conveyor CVD system that enables rapid graphene synthesis using liquid precursors. Pristine and nitrogen-doped graphene samples of a size comparable to a smartphone (15 cm × 5 cm) are successfully synthesized at temperatures of 900, 950, and 1000 °C using butane and pyridine, respectively. Raman spectroscopy allows optimization of the rapid-synthesis conditions to achieve uniformity and high quality. By conducting compositional analysis via X-ray photoelectron spectroscopy as well as electrical characterization, it is confirmed that graphene synthesis and nitrogen doping degree can be adjusted by varying the synthesis conditions. Testing the corresponding graphene samples as gas-sensor channels for NH3 and NO2 and evaluating their response characteristics show that the gas sensors exhibit polar characteristics in terms of gas adsorption and desorption depending on the type of gas, with contrasting characteristics depending on the presence or absence of nitrogen doping; nitrogen-doped graphene exhibits superior gas-sensing sensitivity and response speed compared with pristine graphene.

The Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISHTO) campaign took place in autumn 2021 at the NCSR Demokritos background high-altitude Helmos Hellenic Atmospheric Aerosol and Climate Change station (HAC)2 to study the interactions between aerosols and clouds. The current study presents the chemical characterization of the non-refractory (NR) PM1 aerosol fraction using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM). A comparative offline aerosol filter analysis by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) showed consistent results regarding the species determined. Source apportionment applied on both datasets (ACSM-ToF and offline AMS analysis on filter extracts) yielded the same factors for the organic aerosol (one primary and two secondary factors). Additionally, the positive matrix factorization (PMF) model was applied on the total PM1 fraction by the ToF-ACSM (including both organic and inorganic ions). Five different types were identified, including a primary organic factor; ammonium nitrate; ammonium sulfate; and two secondary organic aerosols, one more oxidized and one less oxidized. The prevailing atmospheric conditions at the station, i.e., cloud presence, influence of emissions from the planetary boundary layer (PBL), and air mass origin, were also incorporated in the study. The segregation between PBL and free-troposphere (FT) conditions was made by combining data from remote sensing and in situ measurement techniques. The types of air masses arriving at the site were grouped as continental, marine, dust, and marine–dust based on back-trajectory data. Significant temporal variability in the aerosol characteristics was observed throughout the campaign; in September, air masses from within the PBL were sampled most of the time, resulting in much higher mass concentrations compared to October and November when concentrations were reduced by a factor of 5. Both in-cloud and FT measurement periods resulted in much lower concentration levels, while a similar composition was observed in PBL and FT conditions. We take advantage of using a recently developed “virtual-filtering” technique to separate interstitial from activated aerosol sampled from a PM10 inlet during cloudy periods. This allows the determination of the chemical composition of the interstitial aerosol during in-cloud periods. Ammonium sulfate, the dominant PMF factor in all conditions, contributed more when air masses were arriving at (HAC)2 during dust events, while a higher secondary organic aerosol contribution was observed when air masses arrived from continental Europe.

Speed restrictions for ships have been introduced locally to reduce the waves and turbulence causing erosion, and safety hazards, and to mitigate the air and underwater noise emissions. Ship speed restrictions could be used to minimize the climate impact of maritime transport since many air pollutants in ship exhaust gas are reduced when travelling at lower speeds. However, for example, methane and black carbon emissions do not linearly correlate with the load of internal combustion engines. Therefore, the effect of speed restrictions may not be trivial. Black carbon concentrations from ship plumes were examined at a remote marine site in the southwestern Finnish archipelago. Ships with service speeds over 15 kn and equipped with an exhaust gas cleaning system were analysed for black carbon emissions as a function of speed. Both unadjusted and weather-adjusted main engine loads were modelled to determine load-based emission factors. Black carbon concentration per kilogram of fuel decreased as a function of engine load. However, calculated per hour, the black carbon emission increased as a function of ship speed, reaching peak values at around 15–20 kn and decreasing thereafter. In terms of local air quality, total black carbon emission per nautical mile was the highest around the halved speeds, 10–13 kn, or when the speed was higher than 20–23 kn. From a climate warming perspective, the CO2 emissions dominated the exhaust gas, and reducing the speed decreased the global warming potential in CO2 equivalent, both per hour and per nautical mile.

The Geostationary Environment Monitoring Spectrometer (GEMS) over Asia is the first geostationary Earth orbit instrument in the virtual constellation of sensors for atmospheric chemistry and composition air quality research and applications. For the first time, the hourly observations enable studies of diurnal variation in several important trace gas and aerosol pollutants including nitrogen dioxide (NO2), which is the focus of this work. NO2 is a regulated pollutant and an indicator of anthropogenic emissions in addition to being involved in tropospheric ozone chemistry and particulate matter formation. We present new quantitative measures of NO2 tropospheric column diurnal variation which can be greater than 50 % of the column amount, especially in polluted environments. The NO2 distribution is seen to change hourly and can be quite different from what would be seen by a once-a-day low-Earth-orbit satellite observation. We use GEMS data in combination with TROPOspheric Monitoring Instrument (TROPOMI) satellite and Pandora ground-based remote sensing measurements and Multi-Scale Infrastructure for Chemistry and Aerosols (Version 0, MUSICAv0) 3D chemical transport model analysis to examine the NO2 diurnal variation in January and June 2023 over Northeast Asia and Seoul, South Korea, study regions to distinguish the different emissions, chemistry, and meteorological processes that drive the variation. Understanding the relative importance of these processes will be key to including pollutant diurnal variation in models aimed at determining true pollutant exposure levels for air quality studies. The work presented here also provides a path for investigating similar NO2 diurnal cycles in the new Earth Venture Instrument-1 Tropospheric Emissions: Monitoring Pollution (TEMPO) data over North America, and later over Europe with Sentinel-4.

Although heart disease stands as a prominent contributor to worldwide deaths, not all individuals affected by it ultimately fall prey to its effects. Timely diagnosis and effective treatment can offer those with heart conditions a high-quality life in their later years. Consequently, early disease detection using accessible medical data has been a central goal for researchers in recent decades. Traditionally, researchers relied on statistical tools for this purpose. However, machine learning algorithms, especially classification models, have gained prominence with the growing accumulated data. These algorithms have shown promise in predicting heart disease based on individual data. Our study employed various classification algorithms to predict heart disease incidence using the available dataset. We prioritized model reliability by incorporating the conformal classifier. Our results have shown that boosting algorithms, such as XGBoost and CatBoost, demonstrated exceptional performance with promising metrics. These models identified chest pain type and ST segment slope as crucial indicators of heart disease. Boosting algorithms exhibited a compelling combination of broad coverage and a small prediction set size, making them well-suited for heart disease prediction. Furthermore, we employed explainable artificial intelligence-boosting algorithms to enhance the interpretability of our predictions.

In this article, we study the role of awareness and its impact on the control of infectious diseases. We analyze a susceptible-infected-recovered model with a media awareness compartment. We find the effective reproduction number R0{R}_{0}. We observe that our model exhibits transcritical forward bifurcation at R0=1{R}_{0}=1. We also performed the sensitivity analysis to determine the sensitivity of parameters of the effective reproduction number R0{R}_{0}. In addition, we study the corresponding optimal control problem by considering control in media awareness and treatment. Our studies conclude that we can reduce the rate of spread of infection in the population by increasing the treatment rate along with media awareness.

A methodology for directly predicting the time evolution of the assumed parameters for distribution densities based on the Liouville equation, as proposed earlier, is extended to multidimensional cases and to cases in which the systems are constrained by integrals over a part of the variable range. The general formulation developed here is applicable to a wide range of problems, including the frequency distributions of subgrid-scale variables, hydrometeor size distributions, and probability distributions characterizing data uncertainties. The extended methodology is tested against a convective energy-cycle system and the Lorenz strange attractor. As a general tendency, the variance tends to collapse to a vanishing value over a finite time, regardless of the chosen assumed distribution form. This general tendency is likely due to a common cause, as the collapse of the variance is commonly found in ensemble-based data assimilation due to low dimensionality.

This study investigates the rain-initiated mixing and variability in the mixing ratio of selected trace gases in the atmosphere over the central Amazon rain forest. It builds on comprehensive data from the Amazon Tall Tower Observatory (ATTO), spanning from 2013 to 2020 and comprising the greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4); the reactive trace gases carbon monoxide (CO), ozone (O3), nitric oxide (NO), and nitrogen dioxide (NO2); and selected volatile organic compounds (VOCs). Based on more than 1000 analyzed rainfall events, the study resolves the trace gas mixing ratio patterns before, during, and after the rain events, along with vertical mixing ratio gradients across the forest canopy. The assessment of the rainfall events was conducted independently for daytime and nighttime periods, which allows us to elucidate the influence of solar radiation. The mixing ratios of CO2, CO, and CH4 clearly declined during rainfall, which can be attributed to the downdraft-related entrainment of pristine air from higher altitudes into the boundary layer, a reduction of the photosynthetic activity under increased cloud cover, and changes in the surface fluxes. Notably, CO showed a faster reduction than CO2, and the vertical gradient of CO2 and CO is steeper than for CH4. Conversely, the O3 mixing ratio increased across all measurement heights in the course of the rain-related downdrafts. Following the O3 enhancement by up to a factor of 2, NO, NO2, and isoprene mixing ratios decreased. The temporal and vertical variability of the trace gases is intricately linked to the diverse sink and source processes, surface fluxes, and free-troposphere transport. Within the canopy, several interactions unfold among soil, atmosphere, and plants, shaping the overall dynamics. Also, the mixing ratio of biogenic VOCs (BVOCs) clearly varied with rainfall, driven by factors such as light, temperature, physical transport, and soil processes. Our results disentangle the patterns in the trace gas mixing ratio in the course of sudden and vigorous atmospheric mixing during rainfall events. By selectively uncovering processes that are not clearly detectable under undisturbed conditions, our results contribute to a better understanding of the trace gas life cycle and its interplay with meteorology, cloud dynamics, and rainfall in the Amazon.

Global warming is amplified in the Arctic. However, numerical models struggle to represent key processes that determine Arctic weather and climate. To collect data that help to constrain the models, the HALO–(𝒜𝒞)3 aircraft campaign was conducted over the Norwegian and Greenland seas, the Fram Strait, and the central Arctic Ocean in March and April 2022. The campaign focused on one specific challenge posed by the models, namely the reasonable representation of transformations of air masses during their meridional transport into and out of the Arctic via northward moist- and warm-air intrusions (WAIs) and southward marine cold-air outbreaks (CAOs). Observations were made over areas of open ocean, the marginal sea ice zone, and the central Arctic sea ice. Two low-flying and one long-range, high-altitude research aircraft were flown in colocated formation whenever possible. To follow the air mass transformations, a quasi-Lagrangian flight strategy using trajectory calculations was realized, enabling us to sample the same moving-air parcels twice along their trajectories. Seven distinct WAI and 12 CAO cases were probed. From the quasi-Lagrangian measurements, we have quantified the diabatic heating/cooling and moistening/drying of the transported air masses. During CAOs, maximum values of 3 K h−1 warming and 0.3 g kg−1 h−1 moistening were obtained below 1 km altitude. From the observations of WAIs, diabatic cooling rates of up to 0.4 K h−1 and a moisture loss of up to 0.1 g kg−1 h−1 from the ground to about 5.5 km altitude were derived. Furthermore, the development of cloud macrophysical (cloud-top height and horizontal cloud cover) and microphysical (liquid water path, precipitation, and ice index) properties along the southward pathways of the air masses were documented during CAOs, and the moisture budget during a specific WAI event was estimated. In addition, we discuss the statistical frequency of occurrence of the different thermodynamic phases of Arctic low-level clouds, the interaction of Arctic cirrus clouds with sea ice and water vapor, and the characteristics of microphysical and chemical properties of Arctic aerosol particles. Finally, we provide a proof of concept to measure mesoscale divergence and subsidence in the Arctic using data from dropsondes released during the flights.

It is necessary to accurately determine the optical properties of highly absorbing black carbon (BC) aerosols to estimate their climate impact. In the past, there has been hesitation about using realistic fractal morphologies when simulating BC optical properties due to the complexity involved in the simulations and the cost of the computations. In this work, we demonstrate that, by using a benchmark machine learning (ML) algorithm, it is possible to make fast and highly accurate predictions of the optical properties for BC fractal aggregates. The mean absolute errors (MAEs) for the optical efficiencies ranged between 0.002 and 0.004, whereas they ranged between 0.003 and 0.004 for the asymmetry parameter. Unlike the computationally intensive simulations of complex scattering models, the ML-based approach accurately predicts optical properties in a fraction of a second. Physiochemical properties of BC, such as total particle size (number of primary particles (Npp), outer volume equivalent radius (ro), mobility diameter (Dm), outer primary particle size (ao), fractal dimension (Df), wavelength (λ), and fraction of coating (fcoating), were used as input parameters for the developed ML algorithm. An extensive evaluation procedure was carried out in this study while training the ML algorithms. The ML-based algorithm compared well with observations from laboratory-generated soot, demonstrating how realistic morphologies of BC can improve their optical properties. Predictions of optical properties like single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved compared to the conventional Mie-based predictions. The results indicate that it is possible to generate optical properties in the visible spectrum using BC fractal aggregates with any desired physicochemical properties within the range of the training dataset, such as size, morphology, or organic coating. Based on these findings, climate models can improve their radiative forcing estimates using such comprehensive parameterizations for the optical properties of BC based on their aging stages.

It has been found that ozone (O3) pollution episodic cases are prone to appear when the Greater Bay Area (GBA) is under the control of typhoons and subtropical high-pressure systems in summer. To prevent this pollution effectively and efficiently, it is essential to understand the contribution of O3 precursors emitted from different periods and areas under these unfavorable weather conditions. In this study, we further extended the Ozone Source Apportionment Technology (OSAT) from the Comprehensive Air Quality Model with Extensions (CAMx) model to include the function of tracking the emission periods of O3 precursors. Subsequently, the updated OSAT module was applied to investigate the spatiotemporal contribution of precursor emissions to the O3 concentration over the GBA in July and August 2016, when several O3 episodic cases appeared in this period. Overall, the emissions within the GBA, from other regions of Guangdong province (GDo), and from the neighboring provinces were the three major contributors, accounting for 23 %, 15 %, and 17 % of the monthly average O3 concentration, respectively. More than 70 % of the O3 on the current day was mainly formed from the pollutants emitted within 3 d, and the same day's emission contributed approximately 30 %. During the O3 episodes, when the typhoon approached, more pollutants emitted 2–3 d before from the GDo and adjacent provinces were transported to the GBA, leading to an increase in O3 concentrations within this region. Under the persistent influence of northerly wind, the pollutants originating from eastern China earlier than 2 d previously can also show a noticeable impact on the O3 over the GBA on the present day, accounting for approximately 12 %. On the other hand, the O3 pollution was primarily attributed to the local emission within 2 d when the GBA was mainly under the influence of the subtropical high-pressure systems. These results indicate the necessity for considering the influence of meteorological conditions in implementing the control measures. Meanwhile, analogous relationships between source area/time and receptor were derived by the zero-out method, supporting the validity of the updated OSAT module. Our approach and findings could offer more spatiotemporal information about the sources of O3 pollution, which could aid in the development of effective and timely control policies.

Abstract Studies of fractional quantum Hall effects (FQHE) across various two-dimensional electronic systems (2DES) have helped to establish the equilibrium FQHE many-body ground states with fractionally charged excitations and composite particles in condensed matter. Then, the question arises whether an FQHE system driven to non-equilibrium can approach a different stationary state from the known equilibrium FQHE states. To investigate this question, we examine FQHE over filling factors, ν, 2 ≥ ν ≥ 1 under non-equilibrium finite bias conditions realized with a supplementary d c-current bias, I D C , in high mobility GaAs/AlGaAs devices. Here, we show that all observable canonical equilibrium FQHE resistance minima at ∣I D C ∣ = 0 undergo bimodal splitting vs. I D C , yielding branch-pairs and diamond shapes in color plots of the diagonal resistance, as canonical FQHE are replaced, with increasing I D C , by excited-state fractionally quantized Hall effects at branch intersections. A tunneling model serves to interpret the results.

Abstract Dichroic techniques are highly relevant in the field of topological materials, layered systems, and spin-polarized electronic states. Dichroism in angle-resolved photoemission is per se a matrix element effect, which depends on the initial and final states as well as on the perturbation by the light field. Although matrix element effects in ARPES such as dichroism are important for addressing properties of the initial state wave functions, the results can strongly depend on experimental geometry or final state effects. Combining experimental data on bulk WSe2 taken at soft x-ray photon energies with state-of-the-art photoemission calculations, we demonstrate that a dichroic observable called time-reversal dichroism remains unaffected against variation of photon energy, light polarization, and the angle of incidence. We demonstrate a direct link of TRDAD obtained with both linearly and circularly polarized photons to the initial state properties indicating its broad applicability. The robustness of this matrix element effect indicates a considerable benefit over other dichroic techniques and encourages further experimental and theoretical investigations.

Abstract The wave equation revealing the wave propagation in chiral phononic crystals, established through force equilibrium law, conceals the underlying physical information, such as the essence of the motion coupling and the inertial amplification effect. This has led to a controversy over the bandgap mechanism. In this article, we theoretically unveil the reason for this controversy, and put forward an alternative approach from wave behavior to formulate the wave equation, offering an alternative pathway to articulate the bandgap physics directly. Based on the physics revealed by our theory method, we identify the obstacles in coupled acoustic and optic branches to widen and lower the bandgap. Then we introduce an approach based on spherical hinges to decrease the barriers, for customizing the bandgap frequency and width. Finally, we validate our proposal through numerical simulation and experimental demonstration.

Abstract In this work we apply deep neural networks to find the non-equilibrium steady state solution to correlated open quantum many-body systems. Motivated by the ongoing search to find more powerful representations of (mixed) quantum states, we design a simple prototypical convolutional neural network and show that parametrizing the density matrix directly with more powerful models can yield better variational ansatz functions and improve upon results reached by neural density operator based on the restricted Boltzmann machine. Hereby we give up the explicit restriction to positive semi-definite density matrices. However, this is fulfilled again to good approximation by optimizing the parameters. The great advantage of this approach is that it opens up the possibility of exploring more complex network architectures that can be tailored to specific physical properties. We show how translation invariance can be enforced effortlessly and reach better results with fewer parameters. We present results for the dissipative one-dimensional transverse-field Ising model and a two-dimensional dissipative Heisenberg model compared to exact values.

Abstract Strongly correlated electron materials are often characterized by competition and interplay of multiple quantum states. For example, in high-temperature cuprate superconductors unconventional superconductivity, spin- and charge-density wave orders coexist. A key question is whether competing states coexist on the atomic scale or if they segregate into distinct regions. Using X-ray diffraction, we investigate the competition between charge order and superconductivity in the archetypal cuprate La2−x BaxCuO4, around x = 1/8-doping, where uniaxial stress restores optimal 3D superconductivity at σ 3D ≈ 0.06 GPa. We find that the charge order peaks and the correlation length along the stripe are strongly reduced up to σ 3D. Upon the increase of stress beyond this point, no further changes were observed. Simultaneously, the charge order onset temperature only shows a modest decrease. Our findings suggest that optimal 3D superconductivity is not linked to the absence of charge stripes but instead requires their arrangement into smaller regions. Our results provide insight into the length scales over which the interplay between superconductivity and charge order takes place.

Abstract Resonant inelastic x-ray scattering (RIXS) is a widely used spectroscopic technique, providing access to the electronic structure and dynamics of atoms, molecules, and solids. However, RIXS requires a narrow bandwidth x-ray probe to achieve high spectral resolution. The challenges in delivering an energetic monochromated beam from an x-ray free electron laser (XFEL) thus limit its use in few-shot experiments, including for the study of high energy density systems. Here we demonstrate that by correlating the measurements of the self-amplified spontaneous emission (SASE) spectrum of an XFEL with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate, we can achieve electronic structure resolutions substantially higher than those normally afforded by the bandwidth of the incoming x-ray beam. We further show how this technique allows us to discriminate between the valence structures of Fe and Fe2O3, and provides access to temperature measurements as well as M-shell binding energies estimates in warm-dense Fe compounds.

Abstract Recent years have seen a surge in research on the role of quantum geometry in condensed matter physics. For instance, the Aharonov-Bohm effect is a physical phenomenon where the vector potential induces a phase shift of electron wavepackets in regions with zero magnetic fields due to an obstruction in space associated with a magnetic flux. A similar effect can be observed in solid-state systems, where the topology of the Berry connection can influence electron dynamics. These are paradigmatic examples of how the dynamics can be affected by the system’s geometry. Here, we show that in chiral-symmetric processes the quantum metric has a measurable effect on the mean chiral displacement of delocalized wavefunctions. This finding is supported by a photonic experiment realizing a topological quantum walk and demonstrates an effect that can be attributed directly to the geometry of the state space.

Abstract The photophysical and photochemical properties of push–pull photoswitches, such as stilbene derivatives, are very sensitive to their surroundings, allowing, e.g., for the control of the spectral properties or alternatively for probing the molecular environment. Here, we investigate how various adsorption motifs of 4-(N, N-Dimethylamino)-4’-nitrostilbene (DANS) on an amorphous glass surface influence its absorption spectra. Particular attention is given to the prominent first bright charge transfer state and the factors governing these modifications. The absorption spectra is simulated using time-dependent density functional theory on a large set of adsorption geometries that exhibit different kinds of molecule–surface interactions. We find that C–H⋯O interactions of the methyl or phenyl moieties with the glass affect the spectrum only marginally, whereas the dispersion interaction of the π system with the surface tends to diminish the intensity of the first absorption band. Moreover, an enhancement of the push–pull properties of DANS and a significant redshift occur whenever O–H⋯O hydrogen bonds with the NO2 group are present, whereas a hydrogen bond O–H⋯N to the NMe2 group results in a blueshift.

Abstract Quantum networks comprised of entangled end nodes serve stronger than the classical correlation for unparalleled quantum internet applications. However, practical quantum networking is affected by noise, which at its worst, causes end nodes to be described by pre-existing classical data. In such untrusted networks, determining quantum network fidelity and genuine multi-node entanglement becomes crucial. Here, we show that determining quantum network fidelity and genuine N-node entanglement in an untrusted star network requires only N + 1 measurement settings. This method establishes a semi-trusted framework, allowing some nodes to relax their assumptions. Our network determination method is enabled by detecting genuine N-node Einstein-Podolsky-Rosen steerability. Experimentally, using spontaneous parametric down-conversion entanglement sources, we demonstrate the determinations of genuine 3-photon and 4-photon quantum networks and the false positives of the widely used entanglement witness, the fidelity criterion of 1/2. Our results provide a scalable method for the determination of multipartite entanglement in realistic quantum networks.

Abstract We design a quantum method for classical information compression that exploits the hidden subgroup quantum algorithm. We consider sequence data in a database with a priori unknown symmetries of the hidden subgroup type. We prove that data with a given group structure can be compressed with the same query complexity as the hidden subgroup problem, which is exponentially faster than the best-known classical algorithms. We moreover design a quantum algorithm that variationally finds the group structure and uses it to compress the data. There is an encoder and a decoder, along the paradigm of quantum autoencoders. After the training, the encoder outputs a compressed data string and a description of the hidden subgroup symmetry, from which the input data can be recovered by the decoder. In illustrative examples, our algorithm outperforms the classical autoencoder on the mean squared value of test data. This classical-quantum separation in information compression capability has thermodynamical significance: the free energy assigned by a quantum agent to a system can be much higher than that of a classical agent. Taken together, our results show that a possible application of quantum computers is to efficiently compress certain types of data that cannot be efficiently compressed by current methods using classical computers.

This study emulates dropsondes to elucidate the extent to which sporadic airborne sondes adequately represent divergence of moisture transport in Arctic atmospheric rivers (ARs). The convergence of vertically integrated moisture transport (IVT) plays a crucial role as it favours precipitation that significantly affects Arctic sea ice properties. Long-range research aircraft can transect ARs and drop sondes to determine their IVT divergence. In order to assess the representativeness of future sonde-based IVT divergence in Arctic ARs, we disentangle the sonde-based deviations from an ideal instantaneous IVT divergence, which result from undersampling by a limited number of sondes and from the flight duration. Our synthetic study uses C3S Arctic Regional Reanalysis (CARRA) reanalyses to set up an idealised scenario for airborne AR observations. For nine Arctic spring ARs, we mimic flights transecting each AR in CARRA and emulate sonde-based IVT representation by picking single vertical profiles. The emulation quantifies IVT divergence observability by two approaches. First, sonde-based IVT and its divergence are compared to the continuous IVT interpolated onto the flight cross-section. The comparison specifies uncertainties of discrete sonde-based IVT variability and divergence. Second, we determine how temporal AR evolution affects IVT divergence values by contrasting time-propagating sonde-based values with the divergence based on instantaneous snapshots. For our Arctic AR cross-sections, we find that coherent wind and moisture variabilities contribute less than 10 % to the total transport. Both quantities are uncorrelated to a great extent. Moisture turns out to be the more variable quantity. We show that sounding spacing greater than 100 km results in errors greater than 10 % of the total IVT along AR cross-sections. For IVT divergence, the Arctic ARs exhibit similar differences in moisture advection and mass convergence across the embedded front as mid-latitude ARs, but we identify moisture advection as being dominant. Overall, we confirm the observability of IVT divergence with an uncertainty of around 25 %–50 % using a sequence of at least seven sondes per cross-section. Rather than sonde undersampling, it is the temporal AR evolution over the flight duration that leads to high deviations in divergence components. In order to realise the estimation of IVT divergence from dropsondes, flight planning should consider not only the sonde positioning, but also the minimisation of the flight duration. Our benchmarks quantify sonde-based uncertainties as essential preparatory work for the upcoming airborne closure of the moisture budget in Arctic ARs.

Numerous studies have investigated the long-term variability in surface solar radiation (SSR) around the world. However, the large disparity in the availability of observational data between developed and less developed/developing countries leads to an under-representation of studies on SSR changes in the latter. This is especially true for South America, where few observational studies have investigated the SSR trends and usually only at a local or regional scale. In this study we use data from 34 stations distributed throughout all of the regions of Brazil to present the SSR trends in the first 2 decades of the 21st century and investigate their associated causes. The stations were grouped into eight composites according to their proximity. Our results show that in north and northeast Brazil a strong dimming occurred, with significant contributions from increasing atmospheric absorption, most likely due to anthropogenic emissions, and increasing cloud cover. In the southeast and midwest regions of Brazil, near-zero trends resulted from competing effects of clear-sky processes (attenuation of solar radiation under cloudless conditions) and strong negative trends in cloud cover. In the southern part of the Amazon and in south Brazil a statistically insignificant brightening was observed, with significant contributions from decreasing biomass burning emissions in the former and competing minor contributions in the latter. These results can help deepen our knowledge and understanding of SSR long-term trends and their causes in South America, reducing the under-representation of this continent when compared with regions like Europe.

Non-methane hydrocarbons (NMHCs) in the marine atmosphere have been studied extensively due to their important roles in regulating atmospheric chemistry and climate. However, very little is known about the distribution and sources of NMHCs in the lower atmosphere over the marginal seas of China. Herein, we characterized the atmospheric NMHCs (C2–C5) in both the coastal cities and the marginal seas of China in the spring of 2021, with a focus on identifying the sources of NMHCs in the coastal atmosphere. The NMHCs in urban atmospheres, especially alkanes, were significantly higher compared to those in the marine atmosphere, suggesting that terrestrial NMHCs may be an important reservoir/source in the marine atmosphere. A significant correlation was observed between the alkane concentrations and the distances from sampling sites to the nearest land or retention of air mass over land, indicating that alkanes in the marine atmosphere are largely influenced by terrestrial inputs through air mass transport. For alkenes, a greater impact from oceanic emissions was determined due to the lower terrestrial concentrations, short atmospheric lifetime, and substantial sea-to-air fluxes of alkenes compared to alkanes (489 ± 454 vs. 129 ± 106 nmol m−2 d−1). As suggested by the positive matrix factorization, terrestrial inputs contributed to 89 % of alkanes and 69.6 % of alkenes in Chinese marginal seas, subsequently contributing to 84 % of the ozone formation potential associated with C2–C5 NMHCs. These findings underscore the significance of terrestrial outflow in controlling the distribution and composition of atmospheric NMHCs in the marginal seas of China.

A series of emission control measures implemented by the Chinese government have effectively reduced air pollution by multiple pollutants in many regions of the country in recent decades. However, the impacts of these control measures on environmental persistent free radicals (EPFRs) and reactive oxygen species (ROSs), the two groups of chemical species that are known to be linked with adverse human health effects, are still not clear. In this study, we investigated the levels, patterns, and sources of EPFRs and gas- and particle-phase ROSs (referred to as G-ROSs and P-ROSs, respectively) in Beijing during the 2015 China Victory Day Parade period when short-term air quality control measures were imposed. EPFRs in the non-control period (NCP) tended to be radicals centered on a mixture of carbon and oxygen, while those in the control period (CP) were mainly oxygen-centered free radicals. The contribution of G-ROSs to the atmospheric oxidizing capacity increased, and that of P-ROSs decreased during the CP compared to the NCP. The strict control measures reduced ambient EPFRs, G-ROSs, and P-ROSs by 18.3 %, 24.1 %, and 46.9 %, respectively; these amounts were smaller than the decreases in most other measured pollutants. Although particle-matter-based air quality control measures have performed well in achieving “Parade Blue”, it is difficult to simultaneously reduce the negative impacts of the atmosphere on human health. The Parade Blue days were largely attributed to the dramatic reduction in secondary aerosols, which were also largely responsible for EPFR and ROS reductions. Compared to the cases during the NCP, the source-sector-based concentrations of PM2.5, EPFRs, G-ROSs, and P-ROSs during the CP were reduced by 78.7 %–80.8 % when coming from secondary aerosols, by 59.3 %–65.0 % when coming from dust sources, by 65.3 %–67.0 % when coming from industrial emissions, and by 32.6 %–43.8 % when coming from vehicle emissions, while concentrations from other sources increased by 1.61 %–71.5 %. Vehicle emissions and other sources may play complex roles in air quality and public health. This insight will prompt policymakers to reevaluate current air quality management strategies to more effectively address the challenges posed by pollutants such as EPFRs and ROSs.

The wet-season atmosphere in the central Amazon resembles natural conditions with minimal anthropogenic influence, making it one of the rare preindustrial-like continental areas worldwide. Previous long-term studies have analyzed the properties and sources of the natural Amazonian background aerosol. However, the vertical profile of the planetary boundary layer (PBL) has not been assessed systematically. Since 2017, such a profile assessment has been possible with the 325 m high tower at the Amazon Tall Tower Observatory (ATTO), located in a largely untouched primary forest in the central Amazon. This study investigates the variability of submicrometer aerosol concentration, size distribution, and optical properties at 60 and 325 m in the Amazonian PBL. The results show significant differences in aerosol volumes and scattering coefficients in the vertical gradient. The aerosol population was well-mixed throughout the boundary layer during the daytime but became separated upon stratification during the nighttime. We also found a significant difference in the spectral dependence of the scattering coefficients between the two heights. The analysis of downdrafts and the related rainfall revealed changes in the aerosol populations before and after rain events, with absorption and scattering coefficients decreasing as optically active particles are removed by wet deposition. The recovery of absorption and scattering coefficients is faster at 325 m than at 60 m. Convective events were concomitant with rapid increases in the concentrations of sub-50 nm particles, which were likely associated with downdrafts. We found that the aerosol population near the canopy had a significantly higher mass scattering efficiency than at 325 m. There was also a clear spectral dependence, with values for λ=450, 525, and 635 nm of 7.74±0.12, 5.49±0.11, and 4.15±0.11 m2 g−1, respectively, at 60 m, while at 325 m the values were 5.26±0.06, 3.76±0.05, and 2.46±0.04 m2 g−1, respectively. The equivalent aerosol refractive index results, which were obtained for the first time for the wet season in the central Amazon, show slightly higher scattering (real) components at 60 m compared to 325 m of 1.33 and 1.27, respectively. In contrast, the refractive index's absorptive (imaginary) component was identical for both heights, at 0.006. This study shows that the aerosol physical properties at 60 and 325 m are different, likely due to aging processes, and strongly depend on the photochemistry, PBL dynamics, and aerosol sources. These findings provide valuable insights into the impact of aerosols on climate and radiative balance and can be used to improve the representation of aerosols in global climate models.

The planetary boundary layer (PBL) over the Tibetan Plateau (TP) exerts a significant influence on regional and global climate, while its vertical structures of turbulence and evolution features remain poorly understood, largely due to the scarcity of observations. This study examines the vertical profile of and daytime variation in the turbulence dissipation rate (ε) in the PBL and free troposphere over the TP using the high-resolution (6 min and 120 m) measurements from a radar wind profiler (RWP) network, combined with hourly data from ERA5 during the period from 1 September 2022 to 31 October 2023. Observational analyses show that the magnitude of ε below 3 km under all-sky conditions exhibits a large spatial discrepancy over the six RWP stations over the TP. Particularly, the values of ε at Minfeng and Jiuquan over the northern TP and at Dingri (alternately Tingri) over the southern TP are roughly an order of magnitude greater than those at Lijiang, Ganzi (alternately Garzê), and Hongyuan over the eastern TP. This could be partially attributed to the difference in land cover across the six RWP stations. In terms of the diurnal variation, ε rapidly intensifies from 09:00 local standard time (LST) to 14:00 LST and then gradually levels off in the late afternoon. Under clear-sky conditions, both ε and the planetary boundary layer height (zi) are greater compared with cloudy-sky conditions, which could be due to the cooling effect of clouds, which reduces the solar irradiation reaching the surface. In the lower PBL (0.3 ≤ z/zi ≤ 0.5), where z is the height above ground level, the dominant influential factor in the development of turbulence is the surface–air temperature difference (Ts−Ta). By comparison, in the upper PBL (0.6 ≤ z/zi ≤ 1.0), both Ts−Ta and vertical wind shear (VWS) affect the development of turbulence. Above the PBL (1.0 < z/zi ≤ 2.0), the shear production resulting from VWS dominates the variation in turbulence. Under cloudy-sky conditions, the reduced Ts−Ta and weakened surface sensible heat flux tend to inhibit the turbulent motion in the PBL. On the other hand, the strong VWS induced by clouds enhances the turbulence above the PBL. The findings obtained here underscore the importance of the RWP network in revealing the fine-scale structures of the PBL over the TP and gaining new insight into the PBL evolution.

Aerosols can cause brightening of stratocumulus clouds, thereby cooling the climate. Observations and models disagree on the magnitude of this cooling, partly because of the aerosol-induced liquid water path (LWP) adjustment, with climate models predicting an increase in the LWP and satellites observing a weak decrease in response to increasing aerosols. With higher-resolution global climate models, which allow the simulation of mesoscale circulations in which stratocumulus clouds are embedded, there is hope to start bridging this gap. In this study, we present boreal summertime simulations conducted with the ICOsahedral Non-hydrostatic (ICON) global storm-resolving model (GSRM). Compared to geostationary satellite data, ICON produces realistic cloud coverage in the stratocumulus regions; however, these clouds look cumuliform, and the sign of LWP adjustments disagrees with observations. We investigate this disagreement with a causal approach, which combines time series with knowledge of cloud processes, allowing us to diagnose the sources of observation–model discrepancies. The positive ICON LWP adjustment results from a superposition of processes, with an overestimated positive response due to (1) precipitation suppression, (2) a lack of wet scavenging, and (3) cloud deepening under a weak inversion, despite (4) small negative influences from cloud-top entrainment enhancement. We also find that precipitation suppression and entrainment enhancement occur at different intensities during the day and the night, implying that daytime satellite studies suffer from selection bias. This causal methodology can guide modelers on how to modify model parameterizations and setups to reconcile conflicting studies concerning the sign and magnitude of LWP adjustments across different data sources.

The tropospheric hydroxyl (TOH) radical is a key player in regulating oxidation of various compounds in Earth's atmosphere. Despite its pivotal role, the spatiotemporal distributions of OH are poorly constrained. Past modeling studies suggest that the main drivers of OH, including NO2, tropospheric ozone (TO3), and H2O(v), have increased TOH globally. However, these findings often offer a global average and may not include more recent changes in diverse compounds emitted on various spatiotemporal scales. Here, we aim to deepen our understanding of global TOH trends for more recent years (2005–2019) at 1×1°. To achieve this, we use satellite observations of HCHO and NO2 to constrain simulated TOH using a technique based on a Bayesian data fusion method, alongside a machine learning module named the Efficient CH4-CO-OH (ECCOH) configuration, which is integrated into NASA's Goddard Earth Observing System (GEOS) global model. This innovative module helps efficiently predict the convoluted response of TOH to its drivers and proxies in a statistical way. Aura Ozone Monitoring Instrument (OMI) NO2 observations suggest that the simulation has high biases for biomass burning activities in Africa and eastern Europe, resulting in a regional overestimation of up to 20 % in TOH. OMI HCHO primarily impacts the oceans, where TOH linearly correlates with this proxy. Five key parameters, i.e., TO3, H2O(v), NO2, HCHO, and stratospheric ozone, can collectively explain 65 % of the variance in TOH trends. The overall trend of TOH influenced by NO2 remains positive, but it varies greatly because of the differences in the signs of anthropogenic emissions. Over the oceans, TOH trends are primarily positive in the Northern Hemisphere, resulting from the upward trends in HCHO, TO3, and H2O(v). Using the present framework, we can tap the power of satellites to quickly gain a deeper understanding of simulated TOH trends and biases.

​​​​​​​Each summer, the Saharan Air Layer (SAL) transports massive amounts of mineral dust across the Atlantic Ocean, affecting weather, climate, and public health over large areas. Despite the considerable impacts of African dust, the causes and impacts of extreme trans-Atlantic African dust events are not fully understood. The “Godzilla” trans-Atlantic dust event of 2020 has been extensively studied, but little is known about other similar events. Here, we examine the June 2015 event, the second strongest trans-Atlantic African dust event that occurred during the summers from 2003–2022. This event was characterized by moderately high dust emissions over western North Africa and an extremely high aerosol optical depth (AOD) over the tropical North Atlantic. The high dust loading over the Atlantic is associated with atmospheric circulation extremes similar to the Godzilla event. Both the African easterly jet (AEJ) and Caribbean low-level jet (CLLJ) have greatly intensified, along with a westward extension of the North Atlantic subtropical high (NASH), all of which favor the westward transport of African dust. The enhanced dust emissions are related to anomalously strong surface winds in dust source regions and reduced vegetation density and soil moisture across the northern Sahel. The dust plume reduced net surface shortwave radiation over the eastern tropical North Atlantic by about 25 W m−2 but increased net longwave flux by about 3 W m−2. In contrast to the Godzilla event, the 2015 event had minor air quality impacts on the US, partially due to the extremely intensified CLLJ that dispersed the dust plume towards the Pacific.

The dispersion of pollutants in the atmosphere, whether from industrial emissions, wildfires, or other sources, poses significant challenges to air quality management and environmental protection. Understanding the behavior of plumes is crucial for predicting their dispersion patterns and potential impacts on human health and the environment. In this work, we present a new plume rise scheme based on heat transport. The idea at the basis of the new algorithm is the same as the actual scheme embedded in the Lagrangian Particle Model SPRAY-WEB. The temperature difference between the ambient and the plume and the vertical velocity of the plume are expressed on a fixed Eulerian grid. The particles are assigned with an equivalent momentum, temperature, mass, and density, transported as scalar quantities with the particles following the Lagrangian description of the motion. This allows us to reproduce the entrainment phenomenon as a mixing of two fluids (environmental air and plume) with different temperatures: the resulting temperature is given by Richmann's law. The results obtained with the old plume rise algorithm and the new one are compared with Briggs (1975) analytical curve in the case of an idealized atmosphere with a neutral stratification and a constant horizontal wind and with experimental data. From the comparison in an ideal atmosphere, it emerged that with the new algorithm, the plume reaches a higher height than with the old one and the asymptotic trend obtained with both models follows the Briggs curve. As for the comparison with the measurements, the results obtained with the new algorithm are in better agreement with the experimental data than the old one.

Nitrous acid (HONO) is an important precursor of OH radicals which affects not only the sinks of primary air pollutants but also the formation of secondary air pollutants, but its source closure in the atmosphere is still controversial due to a lack of experiment validation. In this study, the HONO budget in Beijing has been analyzed and validated through the coronavirus disease (COVID-19) lockdown event, which resulted in a significant reduction in air pollutant emissions, providing a rare opportunity to understand the HONO budget in the atmosphere. We measured HONO and related pollutants from 1 January to 6 March 2020, which covered the Chinese New Year (CNY) and the COVID-19 lockdown. The average concentration of HONO decreased from 0.97 ± 0.74 ppb before CNY to 0.53 ± 0.44 ppb during the COVID-19 lockdown, accompanied by a sharp drop in NOx and the greatest drop in NO (around 87 %). HONO budget analysis suggests that vehicle emissions were the most important source of HONO during the nighttime (53 ± 17 %) before CNY, well supported by the decline in their contribution to HONO during the COVID-19 lockdown. We found that the heterogeneous conversion of NO2 on ground surfaces was an important nighttime source of HONO (31 ± 5 %), while that on aerosol surfaces was a minor source (2 ± 1 %). Nitrate photolysis became the most important daytime source during the COVID-19 lockdown compared with that before CNY, resulting from the combined effect of the increase in nitrate and the decrease in NO. Our results indicate that reducing vehicle emissions should be an effective measure for alleviating HONO in Beijing.