The contribution of non-exhaust emissions has become comparable to exhaust emissions because of strengthened legislations on the engine. This shift prompted the European Commission to work on the Euro 7 legislation, introducing new requirements including particles from mechanical brakes abrasion. Specific studies on heavy-duty friction materials are not so well represented yet. This study has for objective to close the gap, using a pin-on-disc tribometer following the same method as used in light-duty work. Transition temperature and emission profiles were mapped for seven heavy-duty friction materials. The results demonstrate a higher proportion of ultrafine particles for all friction materials after reaching a transition temperature. The transition temperature ranges from 150 to 230 °C. A clear difference between particle size distribution before and after the transition temperature is shown, with some materials displaying a 99% proportion of ultrafine particles. To illustrate the complexity of understanding the emission profiles, one material displays the lowest particle mass while having one of the highest particle number, leading to a dilemma when it comes to choosing a safe solution. To tackle this complexity, a desirability index method is proposed to rank these materials based on six parameters relating to tribological performances, particulate emissions and potential health effects. The full-system index identified HDV1 as the best of the seven candidates with a score of 0.49, while HDV6 scored a mere 0 on multiple criteria. The study concludes with the potential for the desirability index method to rank materials, including the transition temperature as an emission profile parameter. • A transition temperature (Tt) up to 230 °C is shown for all tested materials. • The Tt is accompanied with a shift towards the emission of nanoparticles. • Emission profiles can be characterised by a desirability index. • The desirability index can be used to rank friction materials.

Decoupling the role of pad materials in brake wear particulate emissions using the UN GTR-24 test method toward non-exhaust PM management.

The altitude-toxicity paradox: Biodiesel blends reduce particulate mass but elevate calculated PAH Toxic equivalency under simulated highland conditions.

The evolution of reacting metal ejecta continues to be a topic of interest at the forefront of metals in reactive and extreme environments. Ejecta are small particles formed when the surface of a metal undergoes Richtmyer–Meshkov instability from a strong shock. Experiments have shown that in the case where ejecta are in ambient conditions that induce a reaction, the ejecta behave irregularly. The ejecta temperature rises and then plateaus, and the acceleration profile shows unexpected jumps. These variations are assumed to be related to the exothermic heat release and particle mass loss caused by the reaction. To explain this phenomenon, efforts to model this in simulations have increased. While current models can capture many of these physical processes, they currently assign a constant reaction shell thickness with little physical reasoning. This work remedies this problem by assigning a dynamic physically informed shell thickness to the reacting particles, using solid analysis. The shell thickness of the particles impacts the rate of change of reacted mass in the system, as well as the rate at which the particles react. The model is based on a simple stress–strain relationship and gives a dynamic assignment for when the reacting particle should begin to fracture. We compare our model to the previous computational and simulation data to analyze the effects of different model parameters.

Gauss–Bonnet lensing of spinning massive particles in static spherically symmetric spacetimes

We investigate neutron stars that contain a unified dark sector composed of cold, degenerate fermionic dark matter and a vacuum-like dark-energy component. Within a general-relativistic two-fluid framework that allows a covariantly conserved, gradient-driven energy exchange between baryons and the dark sector, we quantify how dark microphysics reshapes global structure when the total gravitational radius need not coincide with the luminous baryonic radius. Using a state-of-the-art baryonic equation of state, we explore the halo-forming mass range for fermionic dark matter with particle masses of 400 MeV and 1 GeV, and we characterize sequences by the difference between the total and luminous radii and by the fractional difference between the total and baryonic masses. We confirm established trends: lighter fermions typically support low-density halos that increase the total radius by several kilometers at nearly fixed mass, whereas masses near 1 GeV tend to shrink halos and make the two radii appreciably closer. Our central new result is that a percent-level vacuum-like admixture markedly reduces halo formation, shrinking the radius difference from several kilometers to sub-kilometer scales and the fractional mass difference to ≲ 1%. Combined gravitational-wave and X-ray observations offer a practical route to bound the halo size and the allowed vacuum-like fraction.

Measurements of sulfuric acid (H2SO4) and sulfur trioxide (SO3) were conducted in Pittsburgh, Pennsylvania, during field campaigns in Fall 2023 and Fall 2024. These measurements identified nocturnal concentrations of H2SO4 comparable to those of daytime values. Nocturnal H2SO4 concentrations were observed to increase by 5 × 105 to 5 × 107 molecules cm-3 above background on 16 of the 31 measurement nights. The median peak concentration during events was 6.5 × 106 molecules cm-3, with a maximum of 1.0 × 108 molecules cm-3, exceeding previously reported nighttime concentrations. Increases in H2SO4 concentrations were positively correlated with the anomalously high SO3 concentrations and condensation sink rates, indicating that the formation of H2SO4 increased to overcome the loss rates to particles. Increases in particulate mass and the mass fraction of metals commonly emitted from coal combustion and steel production were also observed. The air masses were traced back to the southeast of Pittsburgh, a region home to a steel mill, coke plant, and a steel processing plant. The observations indicate a previously unrecognized nighttime formation pathway for H2SO4, potentially from heterogeneous catalysis with metal or black carbon, originating from steel and coke plant emissions. Further measurements are needed to identify key compounds and chemical processes driving these increases in nocturnal H2SO4 concentrations.

Dark matter dominates the matter content of the Universe, and its properties can be constrained through large-scale structure probes such as the cross-correlation between the unresolved gamma-ray background (UGRB) and weak gravitational lensing. We analysed 15 years of Fermi–LAT data, constructing UGRB intensity maps in ten energy bins (0.5–1000 GeV), and cross-correlated them with KiDS-Legacy shear in six tomographic bins. The measurements were performed using angular power spectra estimated with the pseudo-C_ v̊angle as functions of mass. We compared our results with bounds from other cosmological tracers and from local probes, and we found them to be complementary, particularly at low masses (̊m GeV/TeV). In addition, using a -like lensing survey cross-correlated with Fermi–LAT, we forecast approximately two to four times tighter limits, highlighting the potential of forthcoming data to strengthen constraints on dark matter annihilation and decay. method. No significant cross-correlation was found. Based on this non-detection, we present 95% upper bounds on the weakly interacting massive particle decay rate Γ_̊m dec and velocity-averaged annihilation cross-section łangleσ_ ̊m ann Euclid

We introduce a plasma wakefield acceleration scheme capable of boosting initially subrelativistic particles to relativistic velocities within millimeter-scale distances. A subluminal light pulse drives a wake whose velocity is continuously matched to the beam speed through a tailored plasma density, thereby extending the dephasing length. We develop a theoretical model that is generalizable across particle mass, initial velocity, and the particular accelerating bucket being used, and we verify its accuracy with particle-in-cell simulations using laser drivers with energies in the joule range.

Biomass power plants (BPPs) are expanding rapidly, yet the most toxicologically potent nanoscale fraction of its particulate emissions remains poorly quantified. Here, in vitro assays demonstrate that nanomagnetite particles (NMPs) constitute a disproportionately toxic subfraction of fine particles: despite contributing only 2.3% of particle mass, NMPs account for 59% of cytotoxicity. On this basis, we quantify NMP emissions from BPPs by integrating measured NMP concentrations with data-augmented machine-learning models and unit-level activities. The resulting global inventory shows strong spatial disparities, with national average concentrations ranging from 150 to over 2000 mg/kg and total global emissions reaching 230 (92-530) t in 2024. Asia contributes 45% of global emissions, followed by South America (26%) and Europe (20%), driven by differences in feedstock composition, installed capacity, and dust removal performance. Scenario projections further indicate that deployment of advanced dust removal technologies under a carbon-neutrality-oriented pathway could reduce global NMP emissions to 76 t by 2050. These results reveal a previously unrecognized source of nanoscale pollution and provide a quantitative framework for integrating NMPs into future bioenergy and air-quality strategies.

Abstract. Aerosol-cloud interactions exert substantial influences on atmospheric chemistry and regional climate, yet process-resolved characterizations of chemical and microphysical evolution within cloud droplets remain limited. Here, two intensive campaigns were conducted at the high-altitude Shanghuang station in southeastern China during autumn 2023 and spring 2024, capturing nocturnal orographic and long-persistence stratiform cloud events. Using two complementary cloud-droplet sampling systems, the ground-based counterflow virtual impactor and a custom-designed aerosol-cloud sampling inlet system, along with aerosol chemical speciation and cloud microphysical measurements, we resolved the composition of interstitial (INT), residual (RES) and ambient (AMB) particles. Organic aerosols (OA) dominated particle mass across both seasons, while inorganic species (nitrate, sulfate, ammonium) exhibited high scavenging efficiencies (≥65%-70%) and strong enrichment in RES particles. Organic components showed seasonally contrasting partitioning patterns, with differences between INT and RES particles indicating variability in aqueous-phase processing. Air-mass analysis further revealed pronounced source-dependent variability, with polluted westerly inflow leading to the highest particle loadings and most aged organic signatures. Linking chemistry with microphysics, we found that secondary organic aerosol (SOA) formation is favored in smaller droplets, whereas primary organic aerosol is preferentially incorporated into larger droplets through collision-coalescence. The contrasting evolution of oxygen-to-carbon ratio in RES and INT particles as a function of OA/ΔCO indicates distinct oxidation pathways for activated and non-activated aerosols. These results demonstrate that droplet size and cloud dynamics jointly regulate aerosol processing and that in-cloud oxidation pathways differ between particle types. This study provides process-level constraints for improving the representation of aqueous-phase SOA formation and aerosol-cloud interactions in atmospheric models, particularly in regions influenced by complex terrain and variable cloud regimes.

ABSTRACT Erosion wear caused by the impact of solid particles in centrifugal slurry pumps presents a significant engineering challenge, affecting pump performance. This study investigates the effects of particle shape, size, and mass flow rate on erosion wear and pump efficiency using ANSYS CFX simulations with the Finnie erosion model. The results demonstrate that increasing the shape factor from 0.2 to 0.8, while keeping the particle mass flow rate at 0.5 kg/s and particle size at 500 µm, reduces erosion wear rate density from 5.23 × 10-5 to 3.26 × 10-5 kg/m2, improving pump performance from 56.87% to 67.35%. Conversely, when the particle size increases from 500 µm to 1500 µm, with a fixed mass flow rate of 0.5 kg/s and shape factor of 0.2, the erosion wear rate density rises from 5.23 × 10-5 to 9.75 × 10-5 kg/m², resulting in a performance drop from 65.85% to 54.45%. Furthermore, increasing the particle mass flow rate from 0.5 kg/s to 1.5 kg/s, with a particle size of 500 µm and shape factor of 0.2, elevates the erosion wear rate density from 5.23 × 10-5 to 7.87 × 10-5 kg/m2, causing pump efficiency to decline from 56.87% to 50.28%. The study concludes that more spherical particles and smaller particle sizes lead to lower erosion rates and better pump performance.

Abstract. Organic aerosols (OA) play a significant role in influencing both climate and human health. However, in source–receptor modelling, a large fraction of OA is typically attributed to highly aged, atmospherically processed species collectively referred to as oxygenated organic aerosol (OOA). Nevertheless, the formation pathways and evolution of OOA as well as their impacts on aerosol optical properties, remain poorly understood. To address this knowledge gap, an experiment was conducted in a suburban site in the Paris region to study the evolution of OOA and their optical properties. Our results show that in regionally transported air masses with mixed biogenic and anthropogenic emissions, the formation of OOA through photochemical processes explains most of the increase in submicron particle mass. Meteorological conditions played a critical role: under dry and strong solar radiation conditions, enhanced formation of more-oxidized OOA (MO-OOA) was observed. BrC absorption increased concurrently, with short-wavelength absorption rising by ∼ 35 % over relatively ∼ 24 h of photochemical aging. Conversely, under humid, low-radiation conditions, the OA composition shifted toward less-oxidized OOA (LO-OOA). Suppressed photochemistry limited MO-OOA production, resulting in a lower overall OA oxidation state. These findings highlight the role of photochemistry in shaping both the chemical evolution and resultant optical properties of OA, underscoring the need to consider meteorological dynamics when evaluating aerosol–climate interactions in suburban forest environments.

To make precision particle mass measurements in charged spectrometers detailed understanding of the influence of detector effects is critical. In this paper the influence of detector-related uncertainties on the determination of the parent particle mass in two-body decays is investigated. It is shown how the dependence of observed mass shifts on the sum and difference of the daughter particle momenta can be used to determine the physical causes of a bias more rigorously than the ad hoc rules that are often adopted. The approach is illustrated using the case of measuring the Λ hyperon mass. This observable is of interest because our current knowledge relies on information from a single experiment that has not been updated to account for changes in the value of the mass used for calibration. With the approach developed in the paper it shown that the LHCb experiment has the capability to make a measurement of the Λ mass with systematic uncertainties from the tracking system controlled to 0.7keV/ . This allows a total precision of 2.2keV/ to be achieved, dominated by the knowledge of the mass used for calibration. This would improve the current knowledge of the Λ hyperon mass by a factor of three.

A bstract We investigate the constraints imposed by the Weak Gravity Conjecture (WGC) on gravitational lensing in gravity’s rainbow, focusing in particular on scenarios beyond extremality and on the interplay between the WGC and the Weak Cosmic Censorship Conjecture (WCCC) in the context of Reissner-Nordström-Anti-de Sitter black holes modified by rainbow gravity. Using topological methods, we first analyze the configuration of photon spheres and confirm that unstable circular photon spheres with topological charge ( ω = −1) exist outside the event horizon throughout the parameter space, thereby verifying the simultaneous validity of both the WGC and the WCCC. The rainbow functions f ( ε ) and g ( ε ), which encode Planck-scale corrections through the energy ratio ( ε = E/E P ), modify both the spacetime metric and the extremality bound. We derive the corresponding modified extremal charge-to-mass ratio, ( q 2 /m 2 ) > ( Q 2 /M 2 ) ext , and show that gravity’s rainbow offers a natural mechanism for reconciling these two fundamental conjectures. By applying the Gauss-Bonnet theorem in conjunction with Jacobi-Maupertuis optical geometry, we compute the weak deflection angles for both photons and massive particles to second order. The rainbow function g ( ε ) appears with powers ( g − 2 ) and ( g − 4 ), enhancing the deflection angle when g ( ε ) < 1, while f ( ε ) influences only the charge-dependent contributions. At extremality, the deflection angle becomes independent of f ( ε ), yielding a universal prediction that can be tested without specifying the form of the rainbow functions. We further find that super-extremal configurations exhibit stronger lensing effects than extremal black holes, suggesting a potential observational discriminator between WGC-satisfying naked singularities and WCCC-preserving black holes. These findings position gravitational lensing as a promising tool for probing quantum-gravity phenomenology with upcoming observational facilities.

Abstract We construct one-particle states as unitary, irreducible representations of Poincare group in front form, characterized by a special null vector, dubbed the reference vector. We demonstrate that this construction has massive-massless continuation. The state is defined by the reference vector. The little group transformation, defined at a general moving momentum, is proved to be equivalent to a change of reference vector. The resulting Wigner D-matrix is parameterized by the rapidities, in addition to the two reference vectors before and after transformation. Boosting the rapidities to infinity, it reaches the massless limit smoothly. We then apply those results to massive spin-1 particle and compute the corresponding Wigner D-matrix. The resulting polarization vectors are equivalent to those in spinor-helicity formalism. In the massless limit, it is shown that longitudinal polarization decouples from the spectrum. The $$\epsilon ^\mu _\pm \rightarrow \epsilon ^\mu _\pm +\xi k^\mu $$ ϵ ± μ → ϵ ± μ + ξ k μ shift turns out to be remnant of this decoupling, with $$\xi $$ ξ determined by the angle between the reference vectors. Our results thus give us a new perspective on gauge symmetry: it can be understood as the equivalence between different massless spin-1 polarization vectors from reaching the massless limit through different reference vectors.

Ammonia (NH3) emissions from concentrated animal feeding operations (CAFOs) are recognized contributors to secondary fine particulate matter (PM2.5) formation, yet empirically derived secondary PM2.5 emission factors applicable to livestock operations remain limited. This study investigated NH3-derived secondary PM2.5 formation under controlled laboratory conditions using a PTFE flow reactor in which NH3 was reacted with sulfur dioxide (SO2) across ammonia-rich NH3:SO2 ratios, with and without zero air. The resulting aerosols were characterized using gravimetric analysis, elemental analysis, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM/EDS), and particle size distribution (PSD) measurements. The recovered particles were dominated by inorganic ammonium–sulfur species, with FTIR and elemental trends indicating sulfite-related intermediates under no-zero-air conditions and more oxidized ammonium–sulfur products under oxygenated conditions. Accounting for both filter-collected and wall-deposited particles, unit particulate emission factors normalized to ammonia input were derived. Size-based apportionment using PSD data indicated that approximately 76.6% of the recovered particulate mass was within the PM2.5 size range. Scaling the experimentally derived unit emission factors using literature-based ammonia emission rates yielded an estimated secondary PM2.5 emission factor of 0.351 ± 0.084 g PM2.5 per animal head per day for cattle feedlots, corresponding to approximately 3–4% of reported total PM2.5 emissions. Because the experimental system isolates NH3–SO2 interactions under idealized conditions and does not represent full atmospheric chemistry, the derived values should be interpreted as screening-level estimates of NH3-derived secondary PM2.5 formation potential intended to support comparative air quality assessments of CAFOs rather than direct predictions of ambient PM2.5 concentrations.

A large fractionof airborne particulate matter consists of secondaryorganic aerosol (SOA), which can be highly viscous, leading to kineticlimitations in gas–particle partitioning and chemical reactivity.The underlying processes, however, have not been fully resolved andquantified in computational models. We use experimental data and thekinetic multilayer model of multiphase chemistry (KM3C) to investigateSOA formation by oxidation of limonene and α-pinene with thenitrate radical (NO3). The model explicitly treats gas–wallloss, gas–particle partitioning, as well as gas- and particle-phasechemistry, and includes a novel method for parametrizing bulk diffusivityfrom particle composition. KM3C utilizes and reproduces the temporalevolution of particle mass and thermal desorption mass spectrometrydata (FIGAERO-CIMS) obtained in chamber experiments. The model canexplain the observed slow evaporation of limonene SOA through slowbulk diffusivity and predicts the formation of a viscous surface crust.In mixed-precursor experiments, KM3C attributes nonadditive SOA massyields to cross-reactions between α-pinene- and limonene-derivedintermediates, leading to accretion products. We conclude that particlephase state, oligomerization, and multiprecursor effects have to beresolved to accurately describe and predict atmospheric SOA formation.

ABSTRACT We present the COLIBRE galaxy formation model and the COLIBRE suite of cosmological hydrodynamical simulations. COLIBRE includes new models for radiative cooling, dust grains, star formation, stellar mass loss, turbulent diffusion, pre-supernova stellar feedback, supernova feedback, supermassive black holes, and active galactic nucleus (AGN) feedback. The multiphase interstellar medium is explicitly modelled without a pressure floor. Hydrogen and helium are tracked in non-equilibrium, with their contributions to the free electron density included in metal-line cooling calculations. The chemical network is coupled to a dust model that tracks three grain species and two grain sizes. In addition to the fiducial thermally driven AGN feedback, a subset of simulations uses black hole spin-dependent hybrid jet/thermal AGN feedback. To suppress spurious transfer of energy from dark matter to stars, dark matter is supersampled by a factor 4, yielding similar dark matter and baryonic particle masses. The subgrid feedback model is calibrated to match the observed $z\approx 0$ galaxy stellar mass function, galaxy sizes, and black hole masses in massive galaxies. The COLIBRE suite includes three resolutions, with particle masses of $\sim 10^5$, $10^6$, and $10^7\, \text{M}_\odot$ in cubic volumes of up to 100, 200, and 400 cMpc on a side, respectively. The largest runs use 136 billion ($5\times 3008^3$) particles. We describe the model, assess its strengths and limitations, and present both visual impressions and quantitative results. Comparisons with various low-redshift galaxy observations generally show very good numerical convergence and excellent agreement with the data.

ABSTRACT We present the calibration of stellar and active galactic nucleus (AGN) feedback in the subgrid model for the new colibre hydrodynamical simulations of galaxy formation. colibre directly simulates the multiphase interstellar medium and the evolution of dust grains, which is coupled to the chemistry. colibre is calibrated at three resolutions: particle masses of $m_{\rm gas} \approx m_{\rm dm} \sim 10^7$ (m7), $10^6$ (m6), and $10^5\,\mathrm{M_\odot }$ (m5). To calibrate the colibre feedback at m7 resolution, we run Latin hypercubes of $\approx 200$ simulations that vary up to four subgrid parameters in cosmological volumes of ($50\,\mathrm{cMpc})^{3}$. We train Gaussian process emulators on these simulations to predict the $z=0$ galaxy stellar mass function (GSMF) and size–stellar mass relation (SSMR) as functions of the model parameters, which we then fit to observations. The trained emulators not only provide the best-fitting parameter values but also enable us to investigate how different aspects of the prescriptions for supernova and AGN feedback affect the predictions. In particular, we demonstrate that while the observed $z=0$ GSMF and SSMR can be matched individually with a relatively simple supernova feedback model, simultaneously reproducing both necessitates a more sophisticated prescription. We show that the calibrated m7 colibre model not only reproduces the calibration target observables, but also matches various other galaxy properties to which the model was not calibrated. Finally, we apply the calibrated m7 model to the m6 and m5 resolutions and, after slight manual adjustments of the subgrid parameters, achieve a similar level of agreement with the observed $z=0$ GSMF and SSMR.