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This study proposed an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. The matching characteristics between aerosol and cloud particle size distributions and gamma distributions were studied using aircraft observation data. The feasibility of the retrieval of the particle effective radius from lidar ratios and backscatter ratios was simulated and studied. A method for inverting the effective radius and number concentration of atmospheric aerosols or small cloud droplets using the backscatter ratio was proposed, and the error sources and applicability of the algorithm were analyzed. This algorithm was suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. Compared with the previous study, this algorithm could quickly obtain the microphysical parameters of atmospheric particles and has good robustness. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 µm. For cloud droplets, it is 1.0–10 µm. An atmospheric-observation experiment was conducted using the multi-wavelength lidar developed by Xi'an University of Technology, and a thin cloud layer was captured. The microphysical parameters of aerosol and clouds during this process were retrieved. The results clearly demonstrate the growth of the effective radius and number concentration.

Lidar at 1064 nm and Ka-band millimetre-wave cloud radar (MMCR) are powerful tools for detecting the height distribution of cloud boundaries and can monitor the entire life cycle of cloud layers. In this study, lidar and MMCR are employed to jointly detect cloud boundaries under different conditions. By enhancing the echo signal of lidar at 1064 nm and combining its signal-to-noise ratio (SNR), the cloud signal can be accurately extracted from the aerosol signals and background noise. The interference signal is eliminated from Doppler spectra of the MMCR by using the noise ratio of the smallest measurable cloud signal (SNRmin⁡) and the spectral point continuous threshold (Nts). Moreover, the quality control of the reflectivity factor of MMCR obtained by the inversion is conducted, which improves the detection accuracy of the cloud signal. We analysed three typical cases studies; case one presents two interesting phenomena: (a) at 19:00–20:00 CST (China standard time), the ice crystal particles at the cloud top boundary are too small to be detected by MMCR, but they are well detected by lidar. (b) At 19:00–00:00 CST, the cirrus cloud changes to altostratus where the cloud particles eventually grow into large sizes, producing precipitation. Further, MMCR has more advantages than lidar in detection of the cloud top boundary within this period. Considering the advantages of the two devices, the change characteristics of the cloud boundary in Xi'an from December 2020 to November 2021 were analysed, with MMCR detection data as the main data and lidar data as the assistant data. The seasonal variation characteristics of clouds show that, in most cases, high clouds often occur in summer and autumn, and the low clouds are usually in winter. The normalized cloud cover shows that the maximum and minimum cloud cover occur in summer and winter, respectively. Furthermore, the cloud boundary frequency distribution results for the whole of the observation period show that the cloud bottom boundary below 1.5 km is more than 1 %, the frequency within the height range of 3.06–3.6 km is approximately 0.38 %, and the frequency above 8 km is less than 0.2 %. The cloud top boundary frequency distribution exhibits the characteristics of a bimodal distribution. The first narrow peak lies at approximately 1.0–3.1 km, and the second peak appears at 6.4–9.8 km.

To further exploit atmospheric cloud water resources (CWRs), it is necessary to correctly evaluate the number of CWRs in an area. The CWRs are hydrometeors that have not participated in precipitation formation at the surface and are suspended in the atmosphere to be exploited and maximise possible precipitation in the atmosphere (Zhou et al., 2020). Three items are included in CWRs: the existing hydrometeors at a certain time, the influx of atmospheric hydrometeors along the boundaries of the study area, and the mass of hydrometeors converted from water vapour through condensation or desublimation, defined as condensate. Condensate constitutes the most important part of CWRs. At present, there is a lack of effective observation methods for atmospheric column condensate evaluation, and direct observation data of CWRs are thus insufficient. A detection method for atmospheric column condensate is proposed and presented. The formation of condensate is closely related to atmospheric meteorological parameters (e.g. temperature and vertical airflow velocity). The amount of atmospheric column condensate can be calculated by the saturated water vapour density and the ascending velocity at the cloud base and top. Active and passive remote sensing technologies are applied to detect the mass of atmospheric column condensate. Combining millimetre cloud radar, lidar and microwave radiometers can suitably observe the vertical velocity and temperature at the cloud boundary. The saturated vapour density can be derived from the temperature, and then, water vapour flux and the maximum possible condensate can be deduced. A detailed detection scheme and data calculation method are presented, and the presented method can realise the determination of atmospheric column condensate. A case of cloud layer change before precipitation is considered, and atmospheric column condensate is deduced and obtained. This is the first application, to our knowledge, of observations for atmospheric column condensate evaluation, which is significant for research on the hydrologic cycle and the assessment of CWRs.

Background. Overfishing and habitat degradation caused a decline of populations of many fish species belonging to the speciose family Sciaenidae. A reliable taxonomic framework is a prerequisite for implementing effective stock management and conservation measures, but phylogeny and taxonomy of the Sciaenidae remain poorly resolved. As traditionally used morphological and single gene-based molecular markers carry a too limited phylogenetic signal for the task, mitochondrial phylogenomics may be a more suitable tool. The freshwater drum, Aplodinotus grunniens Rafinesque, 1819, is one of the few Sciaenidae species that live in freshwater habitats, which makes it an important model for studying the phylogeny and evolution of Sciaenidae. Materials and methods. We sequenced and characterized its mitogenome, and reconstructed the phylogeny of Sciaenidae using mitogenomes of 28 species. Results. The architecture of the mitogenome (16487 bp in length) is standard for this family, and three typical elements were identified in the control region: extended termination associated sequences, central conserved region, and conserved sequence block. Poor availability of sciaenid mitogenomes (especially those belonging to different lineages) prevented us from resolving the phylogeny of this family with confidence. Notably, our results indicate that Larimichthys and Collichthys species may belong to a single genus, and we suspect that the mitogenome of Chrysochir aureus (Richardson, 1846) has been misidentified taxonomically, and urge its resequencing. Conclusion. The sequencing of additional mitogenomes belonging to non-represented and poorly represented lineages is needed to facilitate the understanding of phylogeny and taxonomy of Sciaenidae.

Climate change will affect both the demand for electrical power and the generating capabilities of hydropower plants. Here the authors investigated the combined impact of these effects in the US Pacific Northwest by considering the dynamics of the regional power grid, where they reveal a profound impact of climate change on power shortfall risk by the year 2035.

Even though dissolved organic carbon (DOC) is the most active carbon (C) cycling in soil organic carbon (SOC) pools, it receives little attention from the global C budget. DOC fluxes are critical to aquatic ecosystem inputs and contribute to the C balance of terrestrial ecosystems, but few ecosystem models have attempted to integrate DOC dynamics into terrestrial C cycling. This study introduces a new process-based model, TRIPLEX-DOC, that is capable of estimating DOC dynamics in forest soils by incorporating both ecological drivers and biogeochemical processes. TRIPLEX-DOC was developed from Forest-DNDC, a biogeochemical model simulating C and nitrogen (N) dynamics, coupled with a new DOC process module that predicts metabolic transformations, sorption/desorption, and DOC leaching in forest soils. The model was validated against field observations of DOC concentrations and fluxes at white pine forest stands located in southern Ontario, Canada. The model was able to simulate seasonal dynamics of DOC concentrations and the magnitudes observed within different soil layers, as well as DOC leaching in the age sequence of these forests. Additionally, TRIPLEX-DOC estimated the effect of forest harvesting on DOC leaching, with a significant increase following harvesting, illustrating that land use change is of critical importance in regulating DOC leaching in temperate forests as an important source of C input to aquatic ecosystems.

Multiple sensors are commonly used for degradation monitoring of critical components. The degradation indicators derived from these sensors are significantly different in terms of scale and interpretation. Since these indicators reflect the same degradation path but have different scales and noise, the fusion of the data corresponding to these indicators is important for the condition monitoring and accurate reliability estimation of the components. In this paper, we develop a unified degradation path that considers statistics-based degradation and physics-based degradation models. We also estimate the reliability of such components. Simulation results show that the unified degradation model approximates the actual degradation path effectively. Additionally, more accurate estimates of reliability are obtained when compared with individual degradation paths.

Volatile organic compounds (VOCs) are often subject to synergistic oxidation by different oxidants in the atmosphere. However, the exact synergistic-oxidation mechanism of atmospheric VOCs and its role in particle formation remain poorly understood. In particular, the reaction kinetics of the key reactive intermediates, organic peroxy radicals (RO2), during synergistic oxidation is rarely studied. Here, we conducted a combined experimental and kinetic modeling study of the nocturnal synergistic oxidation of α-pinene (the most abundant monoterpene) by O3 and NO3 radicals as well as its influences on the formation of highly oxygenated organic molecules (HOMs) and particles. We find that in the synergistic O3 + NO3 regime, where OH radicals are abundantly formed via decomposition of ozonolysis-derived Criegee intermediates, the production of CxHyOz HOMs is substantially suppressed compared to that in the O3-only regime, mainly because of the depletion of α-pinene RO2 derived from ozonolysis and OH oxidation by those arising from NO3 oxidation via cross reactions. Measurement–model comparisons further reveal that the cross-reaction rate constants of NO3-derived RO2 with O3-derived RO2 are on average 10–100 times larger than those of NO3-derived RO2 with OH-derived RO2. Despite a strong production of organic nitrates in the synergistic-oxidation regime, the substantial decrease in CxHyOz HOM formation leads to a significant reduction in ultralow- and extremely low-volatility organic compounds, which significantly inhibits the formation of new particles. This work provides valuable mechanistic and quantitative insights into the nocturnal synergistic-oxidation chemistry of biogenic emissions and will help to better understand the formation of low-volatility organic compounds and particles in the atmosphere.

This study aimed to investigate the performance of Multicarrier Phase Coding (MCPC) and P4-encoded waveforms. Researchers explored the unique properties of these signals, focusing on aspects like phase distribution, autocorrelation, power spectral density for P4 encoding, and aperiodic autocorrelation and ambiguity function for MCPC signals. The findings identified optimal MCPC sequences with reduced peak-to-mean envelope power ratios (PMEPR), improving signal performance. Complementary codes based on permutation were also generated and analyzed for MCPC sequences. The study utilized an improved genetic algorithm to develop new and improved waveforms, underscoring the importance of techniques like optimal sequence permutation, complementary sequences, and classical window frequency weighting in enhancing signal performance.

Nowadays, photogrammetrically derived point clouds are widely used in many civilian applications due to their low cost and flexibility in acquisition. Typically, photogrammetric point clouds are assessed through reference data such as LiDAR point clouds. However, when reference data are not available, the assessment of photogrammetric point clouds may be challenging. Since these point clouds are algorithmically derived, their accuracies and precisions are highly varying with the camera networks, scene complexity, and dense image matching (DIM) algorithms, and there is no standard error metric to determine per-point errors. The theory of internal reliability of camera networks has been well studied through first-order error estimation of Bundle Adjustment (BA), which is used to understand the errors of 3D points assuming known measurement errors. However, the measurement errors of the DIM algorithms are intricate to an extent that every single point may have its error function determined by factors such as pixel intensity, texture entropy, and surface smoothness. Despite the complexity, there exist a few common metrics that may aid the process of estimating the posterior reliability of the derived points, especially in a multi-view stereo (MVS) setup when redundancies are present. In this paper, by using an aerial oblique photogrammetric block with LiDAR reference data, we analyze several internal matching metrics within a common MVS framework, including statistics in ray convergence, intersection angles, DIM energy, etc. We associate these metrics to the per-point errors evaluated through LiDAR reference data and discuss their potential contributions in estimating internal reliabilities of point clouds derived from DIM algorithms. The experimental results show that ray convergence and DIM energy are relevant indicators for the accuracy of the generated point clouds. Initial investigation shows that these two indicators could be further utilized to infer the measurement errors without reference data, which could potentially estimate the reliabilities of point clouds through error propagation.

Abstract Transport properties of silicate melts control magma ocean dynamics on the early terrestrial planets and rocky exoplanets. Here we calculate the viscosity (transport of momentum) of peridotite liquid at potential magma ocean conditions (0–159 GPa, 2,200–6,000 K) using ab initio molecular dynamics simulations. We find that, unlike MgSiO3 or basaltic melts, the viscosity of the highly depolymerized peridotite liquid (a) increases monotonically with pressure without an anomalous drop and (b) is lower than those of other melts over the entire mantle pressure range. Low viscosity would promote fractional crystallization in a less polymerized magma ocean and thus contribute to mantle heterogeneity from its earliest stage. Given the compositional dependence of magma ocean properties, emphasis on multicomponent bulk silicate Earth‐like composition, instead of simple end‐members, are rendered necessary, in order to better understand high‐energy planetary accretion processes and their aftermaths.

Medium entropy alloys (MEAs) have a high potential in industrial applications due to their excellent mechanical properties. Here we report a strategy to improve the ductility of the Ni40Co30Cr20Al5Ti5 MEAs by rapid solidification (RS). The as-cast alloy is composed of dendritic structure and L12 nano-precipitates. After RS, the lattice misfit of precipitate and matrix is reduced from 0.251 % to 0.167 %, and the size of the precipitate decreases from 85 nm to 28 nm. Meanwhile, RS also reduces the grain size of matrix. Gliding dislocation can cut through precipitates with low lattice misfit and smaller size, which can avoid strain accumulation and prevent crack initiation at the precipitate-matrix interfaces. Compared with the as-cast alloy, the ductility of the RS alloy is increased by 17 %–42 % without a decrease in strength. Our results can provide a guidance for other experiments using the RS technology (laser cladding, magnetron sputtering, etc.) to achieve the strength-ductility balance in the MEAs.

Acylperoxy radicals (RO2) are key intermediates in the atmospheric oxidation of organic compounds and different from the general alkyl RO2 radicals in reactivity. However, direct probing of the molecular identities and chemistry of acyl RO2 remains quite limited. Here, we report a combined experimental and kinetic modeling study of the composition and formation mechanisms of acyl RO2, as well as their contributions to the formation of highly oxygenated organic molecules (HOMs) during ozonolysis of α-pinene. We find that acyl RO2 radicals account for 67 %, 94 %, and 32 % of the highly oxygenated C7, C8, and C9 RO2, respectively, but only a few percent of C10 RO2. The formation pathway of acyl RO2 species depends on their oxygenation level. The highly oxygenated acyl RO2 (oxygen atom number ≥6) are mainly formed by the intramolecular aldehydic H shift (i.e., autoxidation) of RO2, while the less oxygenated acyl RO2 (oxygen atom number ) are basically derived from the C–C bond cleavage of alkoxy (RO) radicals containing an α-ketone group or the intramolecular H shift of RO containing an aldehyde group. The acyl-RO2-involved reactions explain 50 %–90 % of C7 and C8 closed-shell HOMs and 14 % of C10 HOMs, respectively. For C9 HOMs, this contribution can be up to 30 %–60 %. In addition, acyl RO2 contribute to 50 %–95 % of C14–C18 HOM dimer formation. Because of the generally fast reaction kinetics of acyl RO2, the acyl RO2 + alkyl RO2 reactions seem to outcompete the alkyl RO2 + alkyl RO2 pathways, thereby affecting the fate of alkyl RO2 and HOM formation. Our study sheds lights on the detailed formation pathways of the monoterpene-derived acyl RO2 and their contributions to HOM formation, which will help to understand the oxidation chemistry of monoterpenes and sources of low-volatility organic compounds capable of driving particle formation and growth in the atmosphere.

Abstract Coral reefs in the Central Indo-Pacific region comprise some of the most diverse and yet threatened marine habitats. While reef monitoring has grown throughout the region in recent years, studies of coral reef benthic cover remain limited in spatial and temporal scales. Here, we analysed 24,365 reef surveys performed over 37 years at 1972 sites throughout East Asia by the Global Coral Reef Monitoring Network using Bayesian approaches. Our results show that overall coral cover at surveyed reefs has not declined as suggested in previous studies and compared to reef regions like the Caribbean. Concurrently, macroalgal cover has not increased, with no indications of phase shifts from coral to macroalgal dominance on reefs. Yet, models incorporating socio-economic and environmental variables reveal negative associations of coral cover with coastal urbanisation and sea surface temperature. The diversity of reef assemblages may have mitigated cover declines thus far, but climate change could threaten reef resilience. We recommend prioritisation of regionally coordinated, locally collaborative long-term studies for better contextualisation of monitoring data and analyses, which are essential for achieving reef conservation goals.

We report an observation of ultrahigh-energy (UHE) gamma rays from the Galactic center (GC) region, using 7 yr of data collected by the High-Altitude Water Cherenkov (HAWC) Observatory. The HAWC data are best described as a point-like source (HAWC J1746-2856) with a power-law spectrum ( ${d}N/{d}E=\phi {\left(E/26\,\mathrm{TeV}\right)}^{\gamma }$ ), where γ = −2.88 ± 0.15 _stat − 0.1 _sys and ϕ = 1.5 × 10 ^−15 (TeV cm ^2 s) ^−1 $\pm {0.3}_{\mathrm{stat}}{\,}_{-{0.13}_{\mathrm{sys}}}^{+{0.08}_{\mathrm{sys}}}$ extending from 6 to 114 TeV. We find no evidence of a spectral cutoff up to 100 TeV using HAWC data. Two known point-like gamma-ray sources are spatially coincident with the HAWC gamma-ray excess: Sgr A* (HESS J1745-290) and the Arc (HESS J1746-285). We subtract the known flux contribution of these point sources from the measured flux of HAWC J1746-2856 to exclude their contamination and show that the excess observed by HAWC remains significant (>5 σ ), with the spectrum extending to >100 TeV. Our result supports that these detected UHE gamma rays can originate via hadronic interaction of PeV cosmic-ray protons with the dense ambient gas and confirms the presence of a proton PeVatron at the GC.

Current chemical transport models fail to reproduce both the concentrations and temporal variations of organic aerosol (OA), especially the secondary organic aerosol (SOA), hindering the identification of major contribution sources. The fact that precursors of intermediate-volatility and semivolatile organic compounds (I/SVOCs) are not included in models has a significant impact on the performance of SOA simulation. Herein, we establish a high-resolution emission inventory of I/SVOCs and by incorporating it into the CMAQ model, concentrations, temporal variations, and spatial distributions of POA and SOA originating from different sources in the Yangtze River Delta (YRD) region of China were simulated. By incorporating I/SVOC emissions into the model, the modeled average SOA concentrations in the region increased by 148 %. Significant model improvements in the simulations of different OA components were demonstrated by comparison with comprehensive observation data. Furthermore, spatial and seasonal variations of different source contributions to OA production have been identified. We found that cooking emissions are predominant sources of POA in the densely populated urban area of the region. I/SVOC emissions from industrial sources are dominant contributors to the SOA formation, followed by those from mobile sources. Our results indicate that future control measures should be specifically tailored on an intraregional scale based on the different source characteristics to achieve the national goal of continuous improvement in air quality. In addition, local source profiles and emission factors of I/SVOCs, as well as SOA formation mechanisms in the model framework must urgently be updated to further improve the model performance and thus the accuracy of source identifications.

Understanding the gas–particle partitioning of semivolatile organic compounds (SVOCs) is of crucial importance in the accurate representation of the global budget of atmospheric organic aerosols. In this study, we quantified the gas- vs. particle-phase fractions of a large number of SVOCs in real time in an urban area of East China with the use of a CHemical Analysis of aeRosols ONline (CHARON) inlet coupled to a high-resolution proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS). We demonstrated the use of the CHARON inlet for highly efficient collection of particulate SVOCs while maintaining the intact molecular structures of these compounds. The collected month-long dataset with hourly resolution allows us to examine the gas–particle partitioning of a variety of SVOCs under ambient conditions. By comparing the measurements with model predictions using instantaneous equilibrium partitioning theory, we found that the dissociation of large parent molecules during the PTR ionization process likely introduces large uncertainties to the measured gas- vs. particle-phase fractions of less oxidized SVOCs, and therefore, caution should be taken when linking the molecular composition to the particle volatility when interpreting the PTR-ToF-MS data. Our analysis suggests that understanding the fragmentation mechanism of SVOCs and accounting for the neutral losses of small moieties during the molecular feature extraction from the raw PTR mass spectra could reduce, to a large extent, the uncertainties associated with the gas–particle partitioning measurement of SVOCs in the ambient atmosphere.

Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers is crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China, calculated with the ISORROPIA model based on observed gas and aerosol compositions. The implementation of the Air Pollution Prevention and Control Action Plan led to −35.8 %, −37.6 %, −9.6 %, −81.0 % and 1.2 % changes of PM2.5, SO42-, NHx, non-volatile cations (NVCs) and NO3- in the Yangtze River Delta (YRD) region during this period. Different from the drastic changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH showed a minor change of −0.24 over the 9 years. Besides the multiphase buffer effect, the opposite effects from the changes of SO42- and non-volatile cations played key roles in determining this minor pH trend, contributing to a change of +0.38 and −0.35, respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, SO2, NOx and NH3 emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by ∼0.19, resulting in 0.04 less NO3- and 0.12 less NH4+ partitioning ratios, which suggests that NH3 and NOx emission controls are effective in mitigating haze pollution in eastern China.

Very-high-energy (0.1–100 TeV) gamma-ray emissions were observed in High-Altitude Water Cherenkov (HAWC) data from the lobes of the microquasar SS 433, making them the first set of astrophysical jets that were resolved at TeV energies. In this work, we update the analysis of SS 433 using 2565 days of data from the HAWC observatory. Our analysis reports the detection of a point-like source in the east lobe at a significance of 6.6 σ and in the west lobe at a significance of 8.2 σ . For each jet lobe, we localize the gamma-ray emission and identify a best-fit position. The locations are close to the X-ray emission sites “e1” and “w1” for the east and west lobes, respectively. We analyze the spectral energy distributions and find that the energy spectra of the lobes are consistent with a simple power law d N / d E ∝ E ^α with $\alpha =-{2.44}_{-0.12-0.04}^{+0.13+0.04}$ and $\alpha =-{2.35}_{-0.11-0.03}^{+0.12+0.03}$ for the east and west lobes, respectively. The maximum energy of photons from the east and west lobes reaches 56 TeV and 123 TeV, respectively. We compare our observations to various models and conclude that the very-high-energy gamma-ray emission can be produced by a population of electrons that were efficiently accelerated.

The origin of high-energy galactic cosmic rays is yet to be understood, but some galactic cosmic-ray accelerators can accelerate cosmic rays up to PeV energies. The high-energy cosmic rays are expected to interact with the surrounding material or radiation, resulting in the production of gamma-rays and neutrinos. To optimize for the detection of such associated production of gamma-rays and neutrinos for a given source morphology and spectrum, a multimessenger analysis that combines gamma-rays and neutrinos is required. In this study, we use the Multi-Mission Maximum Likelihood framework with IceCube Maximum Likelihood Analysis software and HAWC Accelerated Likelihood to search for a correlation between 22 known gamma-ray sources from the third HAWC gamma-ray catalog and 14 yr of IceCube track-like data. No significant neutrino emission from the direction of the HAWC sources was found. We report the best-fit gamma-ray model and 90% CL neutrino flux limit from the 22 sources. From the neutrino flux limit, we conclude that, for five of the sources, the gamma-ray emission observed by HAWC cannot be produced purely from hadronic interactions. We report the limit for the fraction of gamma-rays produced by hadronic interactions for these five sources.

The first TeV γ -ray source with no lower energy counterparts, TeV J2032+4130, was discovered by HEGRA. It appears in the third HAWC catalog as 3HWC J2031+415 and it is a bright TeV γ -ray source whose emission has previously been resolved as two sources: HAWC J2031+415 and HAWC J2030+409. While HAWC J2030+409 has since been associated with the Fermi Large Area Telescope Cygnus Cocoon, no such association for HAWC J2031+415 has yet been found. In this work, we investigate the spectrum and energy-dependent morphology of HAWC J2031+415. We associate HAWC J2031+415 with a γ -ray binary system containing the pulsar PSR J2032+4127 and its companion MT91 213. We study HAWC data to observe their periastron in 2017. Additionally, we perform a combined multiwavelength analysis using radio, X-ray, and γ -ray emission. We conclude that HAWC J2031+415 and, by extension, TeV J2032+4130 are most probably a pulsar wind nebula powered by PSR J2032+4127.

We present the most precise measurements to date for the spatial extension and energy spectrum of the γ -ray region between a pulsar’s wind nebula and the interstellar medium, better known as the halo, present around Geminga and PSR B0656+14 (Monogem) using ∼2398 days of >1 TeV data collected by the HAWC observatory. We interpret the data using a physically motivated model for the diffuse γ -ray emission generated from positrons and electrons (e ^± ) injected by the pulsar wind nebula and inverse Compton scattering with interstellar radiation fields. We find the morphologies of the regions inside these halos are characterized by an inhibited diffusion that are approximately three orders of magnitudes smaller than the Galactic average. We also obtain the e ^± emission efficiencies of 6.6% and 5.1%, respectively, for Geminga and Monogem. These results have remarkable consequences for the study of the particle diffusion in the region between the pulsar wind nebulae and the interstellar medium, and for the interpretation of the flux of positrons measured by the AMS-02 experiment above 10 GeV.

This paper investigates the origin of the γ -ray emission from MGRO J1908+06 in the GeV–TeV energy band. By analyzing the data collected by the Fermi Large Area Telescope, the Very Energetic Radiation Imaging Telescope Array System, and High Altitude Water Cherenkov, with the addition of spectral data previously reported by LHAASO, a multiwavelength study of the morphological and spectral features of MGRO J1908+06 provides insight into the origin of the γ -ray emission. The mechanism behind the bright TeV emission is studied by constraining the magnetic field strength, the source age, and the distance through detailed broadband modeling. Both spectral shape and energy-dependent morphology support the scenario that inverse Compton emission of an evolved pulsar wind nebula associated with PSR J1907+0602 is responsible for the MGRO J1908+06 γ -ray emission with a best-fit true age of T = 22 ± 9 kyr and a magnetic field of B = 5.4 ± 0.8 μ G, assuming the distance to the pulsar d _PSR = 3.2 kpc.

The High-Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory, located on the side of the Sierra Negra volcano in Mexico, has been fully operational since 2015. The HAWC collaboration has recently significantly improved their extensive air shower reconstruction algorithms, which has notably advanced the observatory performance. The energy resolution for primary gamma rays with energies below 1 TeV was improved by including a noise-suppression algorithm. Corrections have also been made to systematic errors in direction fitting related to the detector and shower plane inclinations, ${ \mathcal O }(0\buildrel{\circ}\over{.} 1)$ biases in highly inclined showers, and enhancements to the core reconstruction. The angular resolution for gamma rays approaching the HAWC array from large zenith angles (>37°) has improved by a factor of 4 at the highest energies (>70 TeV) as compared to previous reconstructions. The inclusion of a lateral distribution function fit to the extensive air shower footprint on the array to separate gamma-ray primaries from cosmic-ray ones based on the resulting χ ^2 values improved the background rejection performance at all inclinations. At large zenith angles, the improvement in significance is a factor of 4 compared to previous HAWC publications. These enhancements have been verified by observing the Crab Nebula, which is an overhead source for the HAWC Observatory. We show that the sensitivity to Crab-like point sources ( E ^−2.63 ) with locations overhead to 30° zenith is comparable to or less than 10% of the Crab Nebula’s flux between 2 and 50 TeV. Thanks to these improvements, HAWC can now detect more sources, including the Galactic center.