Transport Model Predictions Research Articles

Observational evidence reveals the significance of nocturnal chemistry in seasonal secondary organic aerosol formation

Oxidized Organic Aerosol (OOA), a major component of fine atmospheric particles, impacts climate and human health. Previous experiments and atmospheric models emphasize the importance of nocturnal OOA formation from NO3· oxidation of biogenic VOCs. This seasonal study extends the understanding by showing that nocturnal oxidation of biomass-burning emissions can account for up to half of total OOA production in fall and winter. It is the first to distinguish nocturnal OOA characteristics from daytime OOA across all seasons using bulk aerosol measurements. Summer observations of nocturnal OOA align well with regional chemistry transport model predictions, but discrepancies in other seasons reveal a common model deficiency in representing biomass-burning emissions and their nocturnal oxidation. This study underscores the significance of near-ground nocturnal OOA production, proposes a method to differentiate it using bulk aerosol measurements, and suggests model optimization strategies. These findings enhance the understanding and prediction of nighttime OOA formation.

Turbulence Intermittency Effects on the Initiation Threshold of Sediment Motion in Natural Waters

AbstractThe initiation threshold of sediment motion, a key component in quantifying sediment transport, has potential link to intermittent turbulence bursts. Here, we elaborated in situ experiments on coastal sea bottom covered with cohesive sediments, to obtain intermittency parameters. The variable “waiting time” between turbulence bursts was utilized to capture the occurrence of sediment initiation events in natural waters. A relationship between waiting time and shear stress reveals the different intermittency features of sediment flux time series before and after reaching the threshold, which can be used to determine the initiation threshold of sediment motion. Multi‐site results demonstrate the limitations of traditional empirical formulae for fine‐grained sediments, where cohesiveness becomes more pronounced as grain size decreases and the deviation can reach 600%. The empirical formula was modified using grain size, and the modified calculations were in good agreement with observed values, which will greatly assist in sediment transport and geomorphology model predictions.

Probabilistic assessment of scalar transport under hydrodynamically unstable flows in heterogeneous porous media

Quantitative predictions of scalar transport in natural porous media is a nontrivial task given the presence of multi-scale spatial heterogeneity in the permeability field. Due to data scarcity, the structural map of the permeability field is subject to uncertainty and therefore, model predictions are uncertain. For such reasons, probabilistic models of flow and transport in natural porous media are required in risk assessment and to provide reliable decision making under uncertainty. Further complexities arise when the viscosity of the injected solute differs from that of the ambient fluid. Under the presence of viscosity contrast, hydrodynamic instabilities give rise to viscous fingering, which induces additional disorder in both velocity and solute concentration fields. This work examines the combined role of viscous fingering and permeability heterogeneity in the probabilistic description of transport predictions. In particular, we focus on metrics that are important for risk analysis, such as the solute plume’s early arrival times and the maximum concentration observed at a given location. We propose to use the Projection Pursuit Adaptation (PPA) method in the Polynomial Chaos Expansion (PCE) framework to quantify uncertainty in transport model predictions. The PPA method is a data-driven approach that optimally represents a given quantity of interest in a low-dimensional manifold. Unlike other dimension reduction techniques in uncertainty quantification, the PPA method utilizes non-linear information of the quantity of interest to identify the low-dimensional manifold, thereby increasing the likelihood of finding a more accurate lower-dimensional space. Moreover, the PPA model converges to the physical solution in a mean squared sense with respect to the polynomial order, enabling the construction of a converged model even with limited available data. Then, the PPA results are compared to Monte Carlo simulations using the same amount of data. This comparison illustrates that while Monte Carlo simulations are able to capture low-order statistics, they struggle to represent more detailed probability density functions. Our results show how the combined effect of permeability heterogeneity and viscosity contrast can enhance the mobility of the solute plume.

Cosmic ray transport in large-amplitude turbulence with small-scale field reversals

ABSTRACT The nature of cosmic ray (CR) transport in the Milky Way remains elusive. The predictions of current microphysical CR transport models in magnetohydrodynamic (MHD) turbulence are drastically different from what is observed. These models usually focus on MHD turbulence with a strong guide field and ignore the impact of turbulent intermittency on particle propagation. This motivates our studying the alternative regime of large-amplitude turbulence with δB/B0 ≫ 1, in which intermittent small-scale magnetic field reversals are ubiquitous. We study particle transport in such turbulence by integrating trajectories in stationary snapshots. To quantify spatial diffusion, we use a set-up with continuous particle injection and escape, which we term the turbulent leaky box. We find that particle transport is very different from the strong guide-field case. Low-energy particles are better confined than high-energy particles, despite less efficient pitch-angle isotropization at small energies. In the limit of weak guide field, energy-dependent confinement is driven by the energy-dependent (in)ability to follow reversing magnetic field lines exactly and by the scattering in regions of ‘resonant curvature’, where the field line bends on a scale that is of the order of the local particle gyro-radius. We derive a heuristic model of particle transport in magnetic folds that approximately reproduces the energy dependence of transport found numerically. We speculate that CR propagation in the Galaxy is regulated by the intermittent field reversals highlighted here and discuss the implications of our findings for CR transport in the Milky Way.

Galactic diffuse gamma rays meet the PeV frontier

Context. The Tibet ASγ and LHAASO collaborations recently reported the observation of a γ-ray diffuse emission with energy up to the PeV level from the Galactic plane. Aims. We discuss the relevance of non-uniform cosmic-ray transport scenarios and the implications of these results for cosmic-ray physics. Methods. We used the DRAGON and HERMES codes to build high-resolution maps and spectral distributions of that emission for several representative models under the condition that they reproduce a wide set of local cosmic-ray data up to 100 PeV. Results. We show that the energy spectra measured by Tibet ASγ, LHAASO, ARGO-YBJ, and Fermi-LAT in several regions of interest in the sky can all be reasonably described in terms of the emission arising by the Galactic cosmic-ray “sea”. We also show that all our models are compatible with IceTop γ-ray upper limits. Conclusions. We compare the predictions of conventional and space-dependent transport models with those data sets. Although the Fermi-LAT, ARGO-YBJ, and LHAASO preliminary data slightly favor this scenario, due to the still large experimental errors, the poorly known source spectral shape at the highest energies, the potential role of spatial fluctuations in the leptonic component, and a possible larger-than-expected contamination due to unresolved sources, a solid confirmation requires further investigations. We discuss which measurements will be most relevant in order to resolve the remaining degeneracy.

\(J/\psi \) and \(\psi (2S)\) Production in Small Systems with PHENIX

The suppression of the $\psi$(2S) nuclear modification factor has been seen as a trademark signature of final state effects in large collision systems for decades. In small systems, deviations of the nuclear modification from unity had been attributed to cold nuclear matter effects until the observation of strong differential suppression of the $\psi$(2S) state in $p/d+$A collisions, which suggests the presence of final state effects. In this paper, we present results of J/$\psi$ and $\psi$(2S) measurements in the dimuon decay channel for $p+p$, $p+$Al, and $p+$Au collision systems at $\sqrt{s_{_{NN}}}$ = 200 GeV. Key results include the nuclear modification factors $R_{pA}$ as a function of centrality and rapidity. The measurements are compared with shadowing and transport model predictions, as well as to complementary measurements at LHC energies.

Application of Optimal Interpolation to Spatially and Temporally Sparse Observations of Aerosol Optical Depth

Aerosol optical depth (AOD) is one of the basic characteristics of atmospheric aerosol. A global ground-based network of sun and sky photometers, the Aerosol Robotic Network (AERONET) provides AOD data with low uncertainty. However, AERONET observations are sparse in space and time. To improve data density, we merged AERONET observations with a GEOS-Chem chemical transport model prediction using an optimal interpolation (OI) method. According to OI, we estimated AOD as a linear combination of observational data and a model forecast, with weighting coefficients chosen to minimize a mean-square error in the calculation, assuming a negligible error of AERONET AOD observations. To obtain weight coefficients, we used correlations between model errors in different grid points. In contrast with classical OI, where only spatial correlations are considered, we developed the spatial-temporal optimal interpolation (STOI) technique for atmospheric applications with the use of spatial and temporal correlation functions. Using STOI, we obtained estimates of the daily mean AOD distribution over Europe. To validate the results, we compared daily mean AOD estimated by STOI with independent AERONET observations for two months and three sites. Compared with the GEOS-Chem model results, the averaged reduction of the root-mean-square error of the AOD estimate based on the STOI method is about 25%. The study shows that STOI provides a significant improvement in AOD estimates.

Measurement of ψ(2S) nuclear modification at backward and forward rapidity in p+p, p+Al , and p+Au collisions at sNN=200 GeV

Suppression of the J/ψ nuclear-modification factor has been seen as a trademark signature of final-state effects in large collision systems for decades. In small systems, the nuclear modification was attributed to cold-nuclear-matter effects until the observation of strong differential suppression of the ψ(2S) state in p+A and d+A collisions suggested the presence of final-state effects. Results of J/ψ and ψ(2S) measurements in the dimuon decay channel are presented here for p+p, p+Al, and p+Au collision systems at sNN=200GeV. The results are predominantly shown in the form of the nuclear-modification factor, RpA, the ratio of the ψ(2S) invariant yield per nucleon-nucleon collision in collisions of proton on target nucleus to that in p+p collisions. Measurements of the J/ψ and ψ(2S) nuclear-modification factor are compared with shadowing and transport-model predictions, as well as to complementary measurements at Large Hadron Collider energies.2 MoreReceived 9 February 2022Accepted 10 May 2022DOI:https://doi.org/10.1103/PhysRevC.105.064912©2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasLeptonic, semileptonic & radiative decaysRelativistic heavy-ion collisionsPhysical SystemsCharmed mesonsHadron collidersMuonsQuarkoniaNuclear Physics

Probing strangeness canonical ensemble with K−, ϕ(1020) and Ξ− production in Au+Au collisions at [formula omitted

We report the first multi-differential measurements of strange hadrons of K−, ϕ and Ξ− yields as well as the ratios of ϕ/K− and ϕ/Ξ− in Au+Au collisions at sNN=3 GeV with the STAR experiment fixed target configuration at RHIC. The ϕ mesons and Ξ− hyperons are measured through hadronic decay channels, ϕ→K+K− and Ξ−→Λπ−. Collision centrality and rapidity dependence of the transverse momentum spectra for these strange hadrons are presented. The 4π yields and ratios are compared to thermal model and hadronic transport model predictions. At this collision energy, thermal model with grand canonical ensemble (GCE) under-predicts the ϕ/K− and ϕ/Ξ− ratios while the result of canonical ensemble (CE) calculations reproduce ϕ/K−, with the correlation length rc∼2.7 fm, and ϕ/Ξ−, rc∼4.2 fm, for the 0-10% central collisions. Hadronic transport models including high mass resonance decays could also describe the ratios. While thermal calculations with GCE work well for strangeness production in high energy collisions, the change to CE at 3 GeV implies a rather different medium property at high baryon density.

Comparison of Scanning LiDAR with Other Remote Sensing Measurements and Transport Model Predictions for a Saharan Dust Case

The evolution and the properties of a Saharan dust plume were studied near the city of Karlsruhe in southwest Germany (8.4298°E, 49.0953°N) from 7 to 9 April 2018, combining a scanning LiDAR (90°, 30°), a vertically pointing LiDAR (90°), a sun photometer, and the transport model ICON-ART. Based on this Saharan dust case, we discuss the advantages of a scanning aerosol LiDAR and validate a method to determine LiDAR ratios independently. The LiDAR measurements at 355 nm showed that the dust particles had backscatter coefficients of 0.86 ± 0.14 Mm−1 sr−1, extinction coefficients of 40 ± 0.8 Mm−1, a LiDAR ratio of 46 ± 5 sr, and a linear particle depolarisation ratio of 0.27 ± 0.023. These values are in good agreement with those obtained in previous studies of Saharan dust plumes in Western Europe. Compared to the remote sensing measurements, the transport model predicted the plume arrival time, its layer height, and its structure quite well. The comparison of dust plume backscatter values from the ICON-ART model and observations for two days showed a correlation with a slope of 0.9 ± 0.1 at 355 nm. This work will be useful for future studies to characterise aerosol particles employing scanning LiDARs.

Source-resolved variability of fine particulate matter and human exposure in an urban area

Abstract. Increasing the resolution of chemical transport model (CTM) predictions in urban areas is important to capture sharp spatial gradients in atmospheric pollutant concentrations and better inform air quality and emissions controls policies that protect public health. The chemical transport model PMCAMx (Particulate Matter Comprehensive Air quality Model with Extensions) was used to assess the impact of increasing model resolution on the ability to predict the source-resolved variability and population exposure to PM2.5 at 36×36, 12×12, 4×4, and 1×1 km resolutions over the city of Pittsburgh during typical winter and summer periods (February and July 2017). At the coarse resolution, county-level differences can be observed, while increasing the resolution to 12×12 km resolves the urban–rural gradient. Increasing resolution to 4×4 km resolves large stationary sources such as power plants, and the 1×1 km resolution reveals intra-urban variations and individual roadways within the simulation domain. Regional pollutants that exhibit low spatial variability such as PM2.5 nitrate show modest changes when increasing the resolution beyond 12×12 km. Predominantly local pollutants such as elemental carbon and primary organic aerosol have gradients that can only be resolved at the 1×1 km scale. Contributions from some local sources are enhanced by weighting the average contribution from each source by the population in each grid cell. The average population-weighted PM2.5 concentration does not change significantly with resolution, suggesting that extremely high resolution PM2.5 predictions may not be necessary for effective urban epidemiological analysis at the county level.

Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation

Data assimilation (DA) combines incomplete background values obtained via chemical transport model predictions with observational information. Several 3-Dimensional variational (3DVAR) and sequential methods (e.g., ensemble Kalman filter (EnKF)) are used to define model errors and build a background error covariance (BEC) and are important factors affecting the prediction performance of DA. The BEC determines the spatial range, where observation concentration is reflected in the model when DA is applied to an air pollution transport model. However, studies investigating the characteristics of BEC using air quality models remain lacking. In this study, horizontal length scale (HLS) and vertical length scale (VLS) analyses of a BEC were applied to EnKF and ensemble square root filter (EnSRF), respectively, and two ensemble-based DA methods were performed; the characteristics were compared with those of a BEC applied to 3DVAR. The results of 6 h PM2.5 predictions performed for 42 days were evaluated for a control run without DA (CTR), 3DVAR, EnKF, and EnSRF. HLS and VLS respectively exhibited a high correlation with the ground wind speed and with the planetary boundary layer height for diurnal and daily variations; EnKF and EnSRF exhibited superior performances among all the methods. The root mean square errors were 11.9 μg m−3 and 11.7 μg m−3 for EnKF and EnSRF, respectively, while those for 3DVAR and CTR were 12.6 μg m−3 and 18.3 μg m−3, respectively. Thus, we proposed a simple method to find a Gaussian function that best described the error correlation of the BEC based on the physical distance.

Kaon flow in Au+Au collisions at 1.23AGeV measured with HADES

We present results on the anisotropic transverse flow of kaons (K+, K0S and K−) in Au+Au collisions at √sNN = 2:42 GeV measured with HADES. It was proposed already in the mid-nineties that kaon flow close to its production threshold might be a good probe for the kaon-nucleon potential and, consequently, or the nuclear equation-of-state. The presented analysis was performed on more than 2 billion events of the 40% most central collisions, which opened the possibility of analyzing the kaon flow differentially as a function of transverse momentum, rapidity, and centrality, even in this low-energy regime. The measurements are compared to microscopic transport model predictions and to other data at similar collision energies. Implications on the properties of compressed nuclear matter will be discussed.

Validation of oil fate and mass balance for the Deepwater Horizon oil spill: Evaluation of water column partitioning

Model predictions of oil transport and fate for the 2010 Deepwater Horizon oil spill (Gulf of Mexico) were compared to field observations and absolute and relative concentrations of oil compounds in samples from 900 to 1400 m depth <11 km from the well. Chemical partitioning analyses using quantitative indices support a bimodal droplet size distribution model for oil released during subsea dispersant applications in June with 74% of the mass in >1 mm droplets that surfaced near the spill site within a few hours, and 1–8% as <0.13 mm microdroplets that remained below 900 m. Analyses focused on 900–1400 m depth <11 km from the well indicate there was substantial biodegradation of dissolved components, some biodegradation in microdroplets, recirculation of weathered microdroplets into the wellhead area, and marine oil snow settling from above 900 m carrying more-weathered particulate oil into the deep plume.

Test Particle Model Predictions of SEP Electron Transport and Precipitation at Mars

AbstractExtreme space weather events can episodically release solar energetic particles (SEPs) that precipitate into planetary atmospheres, leading to aurora and increased ionization. While the induced magnetosphere of Mars does not substantially obstruct SEP protons, the effect on SEP electrons is not known. We use a test particle model modified for relativistic electrons to model transport of 10–200 keV electrons from outside the bow shock and deep in the magnetotail of Mars. We find a substantial influence of curvature and gradient drifts on precipitation, leading to depletions in the bow shock and transport onto closed field lines. The model estimates ∼3% of incident flux precipitates into the Mars atmosphere for a typical SEP event under nominal solar wind conditions, exceeding the estimate from the guiding center path approximation without drift terms. Precipitation is globally patchy. The model estimates 55% of electrons precipitating into cusps along open field lines and 45% precipitating on closed field lines, suggesting drift and nonadiabatic transport mechanisms have a significant influence on precipitation. We also predict that the fraction of precipitating differential flux increases as a function of energy. We discuss how these predictions would be affected by disturbed conditions that tend to accompany the arrival of SEPs and by differing SEP electron spectra hardness and anisotropy. We finally discuss how the simulation predictions compare to observations of diffuse aurora.

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Examination of stiff ion temperature gradient mode physics in simulations of DIII-D H-mode transport

A systematic evaluation of gyrokinetic and gyrofluid model predictions of ion temperature gradient (ITG) stability and transport using parameters from DIII-D high confinement mode (H-mode) plasmas has been performed. The nonlinear CGYRO code is used to make the gyrokinetic predictions, and the quasilinear TGLF model for the corresponding gyrofluid predictions. The assessments are made at three radii (normalized toroidal flux ρ tor = 0.4, 0.55, and 0.7) in three different plasma scenarios with varying levels of neutral beam heating and torque. For each of the nine cases (3 radii × 3 scenarios) considered, ITG turbulence is found to be the dominant long-wavelength instability and transport mechanism. The inclusions of both transverse magnetic fluctuations and dynamic fast beam ions are stabilizing for all cases considered, with strongest effects seen at ρ or = 0.4 where the fast ion population and normalized plasma pressure β = 2μ 0 nT/B 2 are highest. The further inclusion of parallel magnetic fluctuations does not have a meaningful impact on the ITG turbulence in these scenarios, but does destabilize (in combination with fast ions) new high-frequency instabilities at ρ tor = 0.4 in the high power scenarios. In each case the linear and nonlinear ITG critical gradients are predicted to be lower than the measured ITG scale lengths and their associated uncertainties. Inclusion of equilibrium flow shear in the transport predictions generally leads to an upshift in effective critical gradient rather than a qualitative change in the predicted stiffness, with stronger responses typically seen in the gyrokinetic predictions than in the gyrofluid results. However, in most cases these upshifted gradients still remain below the measured values and their uncertainties. Although the predicted critical gradients are below the measured gradients, both models predicted flux-matching gradients consistent with measured values in six of the nine cases considered, with no clear systematic over- or underprediction. Thus, while the experimental ion temperature profiles do not appear to be closely pinned to the ITG critical gradient, both gyrokinetic and gyrofluid models are able to accurately match the measured gradients reasonably well in most cases.

Accuracy of bed-load transport models in eddy-resolving simulations

This work investigates the accuracy of commonly used bed-load transport models when applied in combination with high-resolution Navier-Stokes solvers. Empirical bed-load models predict the transport rate of sediments based on the average bottom shear-stress, while eddy-resolving approaches allow for a space- and time-dependent description of the bottom shear-stress distribution. We discuss the effect that a fine-graining of the stress distribution provided by the flow solver has on the transport model prediction, and we examine the space and time scales at which the averaged values of the transport rate, obtained using the local stress distribution, converge to the transport rate predicted using the average stress. To this aim, we performed Direct Numerical Simulation of a channel flow and used the resulting database to mimic Wall-Resolved and Wall-Modelled Large-Eddy Simulations. We compared the prediction of several bed-load transport models to experimental measurements in order to identify and highlight the limitations that stem from the coupling of these models with eddy-resolving techniques. We find that for small values of the Shields parameter (ratio of viscous and gravitational forces) the fine spatial and temporal resolution of wall-resolved simulations can yield overestimation of the bed-load transport rate; whereas more coarse-grained methods, such as wall-modelled Large Eddy Simulation, result in improved predictions. We also show that a short-time averaging of the force exerted by the fluid on the sediments, which we tested in three different configurations (channel flow with smooth and rough walls and flow over an idealized two-dimensional river dune), improves the accuracy of the bed-load transport predictions, thus providing indications about the flow scales that control the transport process.

Transport model predictions of 225Ac production cross sections via energetic p, d and α irradiation of 232Th targets

Monte Carlo transport codes PHITS and MCNP6 were used to calculate the production cross sections of 225,227Ac, 227,229Th, 223,225Ra, and 229,230,231Pa via the bombardment of a232Th target with energetic protons, deuterons, and α-particles. The incident projectile energies ranged between 10 and 800 MeV/nucleon. When possible, the predicted production cross sections were compared with the available experimental data and other predictions. The degree of the codes' abilities to match the measured data provides a qualitative assessment of the codes’ abilities to predict data from similar, but unmeasured, projectile/target systems. In addition, a comparison between calculated cross sections and data may provide insight into possible improvements in the physics models employed by those transport codes.

Measurements of {Xi }{^-} and overline{Xi }{^+} production in proton\u2013proton interactions at sqrt{s_{NN}} = 17.3\xa0hbox {Ge}hbox {V} in the NA61/SHINE\xa0experiment

The production of Xi (1321)^{-} and overline{Xi }(1321)^{+} hyperons in inelastic p+p interactions is studied in a fixed target experiment at a beam momentum of 158 hbox {Ge}hbox {V}!/!c. Double differential distributions in rapidity {y} and transverse momentum p_{T} are obtained from a sample of 33M inelastic events. They allow to extrapolate the spectra to full phase space and to determine the mean multiplicity of both {Xi }{^-} and overline{Xi }{^+} . The rapidity and transverse momentum spectra are compared to transport model predictions. The {Xi }{^-} mean multiplicity in inelastic p+p interactions at 158 hbox {Ge}hbox {V}!/!c is used to quantify the strangeness enhancement in A+A collisions at the same centre-of-mass energy per nucleon pair.