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Urban sprawl, a consequence of urban growth, profoundly impacts land use/land cover, particularly in regions like the Brazilian Atlantic Forest, as this Biome hosts most of the Brazilian population and is recognized as a global biodiversity hotspot. This study uses geospatial techniques, the Cellular Automata model, and structural landscape metrics to simulate future urban land use changes for 2050. The simulation suggests a significant increase in urban areas by 2050, changing from 32.1% in 2020 to nearly 43% by 2050, mainly encroaching upon agricultural lands. Conversely, forest fragments are projected to decline (lost 3% of areas), and the connectivity analysis highlighted the loss along the rivers, emphasizing the need for proactive conservation strategies. Preserving periurban agriculture is vital for food security and sustainable development, while innovative management of riparian ecosystems enhances urban biodiversity and citizen well-being. Sustainable urban planning and conservation efforts are imperative to mitigate the adverse effects of urban sprawl and foster resilient cities. This research provides crucial insights for decision-makers aiming to balance urban development with environmental preservation in the face of rapid urbanization.

Abstract We report multi-differential measurements of strange hadron production ranging from mid- to target-rapidity in Au+Au collisions at a center-of-momentum energy per nucleon pair of s NN $$ \sqrt{s_{\textrm{NN}}} $$ = 3 GeV with the STAR experiment at RHIC. K S 0 $$ {K}_S^0 $$ meson and Λ hyperon yields are measured via their weak decay channels. Collision centrality and rapidity dependences of the transverse momentum spectra and particle ratios are presented. Particle mass and centrality dependence of the average transverse momenta of Λ and K S 0 $$ {K}_S^0 $$ are compared with other strange particles, providing evidence of the development of hadronic rescattering in such collisions. The 4π yields of each of these strange hadrons show a consistent centrality dependence. Discussions on radial flow, the strange hadron production mechanism, and properties of the medium created in such collisions are presented together with results from hadronic transport and thermal model calculations.

A new long-term emission inventory called the Inversed Emission Inventory for Chinese Air Quality (CAQIEI) was developed in this study by assimilating surface observations from the China National Environmental Monitoring Centre (CNEMC) using an ensemble Kalman filter (EnKF) and the Nested Air Quality Prediction Modeling System. This inventory contains the constrained monthly emissions of NOx, SO2, CO, primary PM2.5, primary PM10, and non-methane volatile organic compounds (NMVOCs) in China from 2013 to 2020, with a horizontal resolution of 15 km × 15 km. This paper documents detailed descriptions of the assimilation system and the evaluation results for the emission inventory. The results suggest that CAQIEI can effectively reduce the biases in the a priori emission inventory, with the normalized mean biases ranging from −9.1 % to 9.5 % in the a posteriori simulation, which are significantly reduced from the biases in the a priori simulations (−45.6 % to 93.8 %). The calculated root-mean-square errors (RMSEs) (0.3 mg m−3 for CO and 9.4–21.1 µg m3 for other species, on the monthly scale) and correlation coefficients (0.76–0.94) were also improved from the a priori simulations, demonstrating good performance of the data assimilation system. Based on CAQIEI, we estimated China's total emissions (including both natural and anthropogenic emissions) of the six species in 2015 to be as follows: 25.2 Tg of NOx, 17.8 Tg of SO2, 465.4 Tg of CO, 15.0 Tg of PM2.5, 40.1 Tg of PM10, and 46.0 Tg of NMVOCs. From 2015 to 2020, the total emissions decreased by 54.1 % for SO2, 44.4 % for PM2.5, 33.6 % for PM10, 35.7 % for CO, and 15.1 % for NOx but increased by 21.0 % for NMVOCs. It is also estimated that the emission reductions were larger during 2018–2020 (from −26.6 % to −4.5 %) than during 2015–2017 (from −23.8 % to 27.6 %) for most of the species. In particular, the total Chinese NOx and NMVOC emissions were shown to increase during 2015–2017, especially over the Fenwei Plain area (FW), where the emissions of particulate matter (PM) also increased. The situation changed during 2018–2020, when the upward trends were contained and reversed to downward trends for the total emissions of both NOx and NMVOCs and the PM emissions over FW. This suggests that the emission control policies may be improved in the 2018–2020 action plan. We also compared CAQIEI with other air pollutant emission inventories in China, which verified our inversion results in terms of the total emissions of NOx, SO2, and NMVOCs and more importantly identified the potential uncertainties in current emission inventories. Firstly, CAQIEI suggested higher CO emissions in China, with CO emissions estimated by CAQIEI (426.8 Tg) being more than twice the amounts in previous inventories (120.7–237.7 Tg). Significantly higher emissions were also suggested over western and northeastern China for the other air pollutants. Secondly, CAQIEI suggested higher NMVOC emissions than previous emission inventories by about 30.4 %–81.4 % over the North China Plain (NCP) but suggested lower NMVOC emissions by about 27.6 %–0.0 % over southeastern China (SE). Thirdly, CAQIEI suggested lower emission reduction rates during 2015–2018 than previous emission inventories for most species, except for CO. In particular, China's NMVOC emissions were shown to have increased by 26.6 % from 2015 to 2018, especially over NCP (by 38.0 %), northeastern China (by 38.3 %), and central China (60.0 %). These results provide us with new insights into the complex variations in air pollutant emissions in China during two recent clean-air actions, which has the potential to improve our understanding of air pollutant emissions in China and their impacts on air quality. All of the datasets are available at https://doi.org/10.57760/sciencedb.13151 (Kong et al., 2023a).

A comprehensive understanding of spatiotemporal runoff changes in the Yarlung Zangbo (YZ) basin in the southern Tibetan Plateau (TP) at a sub-basin scale, amidst varying climatic and cryospheric conditions, is imperative for effective water resources management. However, spatiotemporal differences of runoff composition and change and their attribution within the YZ basin have not been extensively explored, primarily due to the lack of hydrometeorological observations, especially in the downstream region. In this study, we investigated historical and future evolution of annual and seasonal total water availability, as well as glacier runoff and snowmelt contributions across six sub-basins of the YZ, with a particular focus on the comparison between the upstream Nuxia (NX) basin and the downstream Nuxia–Pasighat (NX-BXK) basin, based on a newly generated precipitation dataset and a well-validated model with streamflow, glacier mass, and snow cover observations. Our findings revealed that large spatiotemporal differences in changes exist within the YZ basin for 1971–2020. Firstly, runoff generation was dominated by rainfall runoff throughout the YZ basin, with glacier runoff playing a more important role in the annual total runoff (19 %) in the NX-BXK sub-basin compared to other sub-basins. Notably, glacier runoff contributed 52 % of the total runoff at the Pasighat outlet of the YZ basin. Secondly, annual runoff exhibited an increasing trend in the NX basin but a decreasing trend in the NX-BXK, primarily attributed to rainfall runoff changes influenced by atmospheric moisture. Glacier runoff enhanced water supply by offsetting the decreasing contribution from rainfall. Total runoff will consistently increase (27–100 mm (10 yr)−1) across the sub-basins through the 21st century, resulting from increased rainfall runoff and a minor effect of increased snowmelt and glacier runoff.

Remote Sensing-based change detection (CD) focuses on the identification of Earth's surface transformations through analysis of multi-temporal satellite images captured for the same geographic region at different points in time. Two common classification-based change detection techniques are post-classification comparison of land cover maps and direct classification of image differences between two periods of interest. In either approach, the selection of an appropriate classifier is critical. Consequently, this study focuses on assessing the performance of different classifiers, including the multi-layer perceptron neural network (MLPNN), support vector machine (SVM), random forest (RF), maximum likelihood (MLH), k-nearest neighbor (KNN), and gaussian naïve bayes (GNB). For this evaluation, two high resolution images captured in 2016 and 2020 by the PS2 sensor within the PlanetScope satellite constellation were used. Additionally, a novel unbiased sampling technique was introduced to selectively capture a minimal number of reference pixels. In the context of change detection, slight variations were observed in classification performance rankings between post-classification and difference image classification methods. However, a consistent trend emerged. The MLPNN consistently achieved the highest accuracy, closely followed by RF and SVM as the second or third-best performers in each technique. In contrast, GNB consistently yielded less favourable results. Importantly, our findings highlight the persistent superiority of the difference image classification in terms of change detection accuracy across all six classifiers. Furthermore, this method offers a significant advantage due to its reduced processing time and computational demands, positioning it as the preferred choice for binary change detection when compared to post-classification techniques.

The Madden–Julian Oscillation (MJO) is a crucial predictability source on a subseasonal-to-seasonal (S2S) timescale. Therefore, the models participating in the World Weather Research Programme and the World Climate Research Programme (WWRP/WCRP) S2S prediction project focus on accurately predicting and analyzing the MJO. This study provides a detailed description of the configuration within the Institute of Atmospheric Physics at the Chinese Academy of Sciences (IAP-CAS) S2S forecast system. We assess the accuracy of the IAP-CAS model's MJO forecast using traditional Real-time Multivariate MJO (RMM) analysis and cluster analysis. Then, we explain the reasons behind any bias observed in the MJO forecast. Comparing the 20-year hindcast with observations, we found that the IAP-CAS ensemble mean has a skill of 24 d. However, the ensemble spread still has potential for improvement. To examine the MJO structure in detail, we use cluster analysis to classify the MJO events during boreal winter into four types: fast-propagating, slow-propagating, standing, and jumping patterns of MJO. The model exhibits biases of overestimated amplitude and faster propagation speed in the propagating MJO events. Upon further analysis, it was found that the model forecasted a wetter background state. This leads to stronger forecasted convection and coupled waves, especially in the fast MJO events. The overestimation of the strength and length of MJO-coupled waves results in a faster MJO mode and quicker dissipation in the IAP-CAS model. These findings show that the IAP-CAS skillfully forecasts signals of MJO and its propagation, and they also provide valuable guidance for improving the current MJO forecast by developing the ensemble system and moisture forecast.

Studies in recent decades have shown strong evidence of physical and biological changes in the Arctic tundra, largely in response to rapid rates of warming. Given the important implications of these changes for ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this great need, scientific understanding of tundra ecology and change remains limited, largely due to the inaccessibility of this region and less intensive studies compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation and active-layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potentially increasing intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled the Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: https://doi.org/10.3334/ORNLDAAC/2177).

Black carbon (BC) plays an important role in air quality, public health, and climate, but its long-term variations in emissions and health effects have been insufficiently understood for China. Here, we present the spatiotemporal evolution of BC emissions and the associated premature mortality in China during 2000–2020 based on an integrated framework combining satellite observations from the Ozone Monitoring Instrument (OMI), an extreme gradient boosting (XGBoost) algorithm, a “top-down” inversion approach, and an exposure–response model. We found that the “bottom-up” approach most likely underestimated BC emissions, particularly in less developed western and remote areas. Pollution controls were estimated to reduce the annual BC emissions by 26 % during 2010–2020, reversing the 8 % growth during 2000–2010. BC emissions in the main coal-producing provinces declined by 2010 but rebounded afterwards. By contrast, provinces with higher economic and urbanization levels experienced emission growth (0.05–0.10 Mg km−2 yr−1) by 2010 and declined greatly (0.07–0.23 Mg km−2 yr−1) during 2010–2020. The national annual BC-associated premature mortality ranged between 733 910 (95 % confidence interval: 676 790–800 250) and 937 980 cases (864 510–1 023 400) for different years. The changing BC emissions contributed to an increase of 78 590 cases (72 520–85 600) during 2000–2005 and a decrease of 133 360 cases (123 150–145 180) during 2010–2015. Strategies differentiated by region are needed for further reducing BC emissions and their health and climate impacts.

We report on the charged-particle multiplicity dependence of net-proton cumulant ratios up to sixth order from s=200 GeV p+p collisions at the Relativistic Heavy Ion Collider (RHIC). The measured ratios C4/C2, C5/C1, and C6/C2 decrease with increased charged-particle multiplicity and rapidity acceptance. Neither the Skellam baselines nor PYTHIA8 calculations account for the observed multiplicity dependence. In addition, the ratios C5/C1 and C6/C2 approach negative values in the highest-multiplicity events, which implies that thermalized QCD matter may be formed in p+p collisions.

This paper proposes a method based on image processing algorithms for ground penetrating radar (GPR) to locate hidden defects in tunnel linings. Firstly, the fast synthetic aperture focusing imaging (Fast-SAFI) algorithm is used to accurately identify the morphology of tunnel-lining defects. Secondly, an iterative algorithm is used to determine the connected regions on the binary image, exclude background noise interference, and locate the centroid and vertices of the correct target connected regions to achieve the positioning of the depth of tunnel-lining defects. To verify the feasibility of the proposed positioning algorithm, a verification experiment was conducted on the experimental wall of the China Academy of Railway Sciences. The experimental results show that the proposed positioning algorithm is reliable and rapid for identifying and locating the morphology and depth of tunnel-lining defects.

Humic-like substances (HULIS) encompass a continuum of molecular weight (MW) ranges, yet our understanding of how HULIS characteristics vary with MW is still limited and not well established. In this study, a combination of ultrafiltration and solid-phase extraction protocols was employed to fractionate the high MW (HMW; > 1 kDa) and low MW (LMW; < 1 kDa) HULIS fractions from ambient aerosols collected during summer and winter at a rural site. Subsequently, comprehensive characterization using total organic carbon, high-performance size exclusion chromatography (HPSEC), UV-visible (UV-vis) and fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR), and negative electrospray ionization high-resolution mass spectrometry (ESI–HRMS) were conducted. The results revealed that HMW HULIS were dominated by larger-sized chromophores, substantially constituting a higher fraction of total organic carbon and UV absorption at 254 nm than LMW HULIS. While both HMW and LMW HULIS shared similar fluorophore types and functional groups, the former exhibited higher levels of humification and a greater presence of polar functional groups (e.g., −COOH; > C=O). HRMS analysis further unveiled that molecular formulas within HMW HULIS generally featured smaller sizes but higher degrees of unsaturation and aromaticity compared to those within LMW HULIS fractions. This observation suggests the possibility of small molecules assembling to form the HMW HULIS through intermolecular weak forces. Moreover, HMW HULIS contained a higher proportion of CHON but fewer CHO compounds than LMW HULIS. In both HMW and LMW HULIS, the unique molecular formulas were primarily characterized by lignin-like species, yet the former displayed a prevalence of N-enriched and highly aromatic species. Additionally, HMW HULIS contained more unique lipid-like compounds, while LMW HULIS exhibited a distinct presence of tannin-like compounds. These findings provide valuable insights into the distribution, optical properties, and molecular-level characteristics of HULIS in atmospheric aerosols, thereby advancing our understanding of their sources, composition, and environmental implications.

Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Rapid decline in Arctic sea ice has created more open water for ocean wave development and highlighted the importance of wave–ice interactions in the Arctic. Some studies have made contributions to our understanding of the potential role of the prognostic floe size distribution (FSD) in sea ice changes. However, these efforts do not represent the full interactions across atmosphere, ocean, wave, and sea ice. In this study, we implement a modified joint floe size and thickness distribution (FSTD) in a newly developed regional atmosphere–ocean–wave–sea ice coupled model and conduct a series of pan-Arctic simulations with different physical configurations related to FSD changes, including FSD-fixed, FSD-varied, lateral melting rate, wave-fracturing formulation, and wave attenuation rate. Firstly, our atmosphere–ocean–wave–sea ice coupled simulations show that the prognostic FSD leads to reduced ice area due to enhanced ice–ocean heat fluxes, but the feedbacks from the atmosphere and the ocean partially offset the reduced ice area induced by the prognostic FSD. Secondly, lateral melting rate formulations do not change the simulated FSD significantly, but they influence the flux exchanges across atmosphere, ocean, and sea ice and thus sea ice responses. Thirdly, the changes in FSD are sensitive to the simulated wave height, wavelength, and wave period associated with different wave-fracturing formulations and wave attenuation rates, and the limited oceanic energy imposes a strong constraint on the response of sea ice to FSD changes. Finally, our results also demonstrate that wave-related physical processes can have impacts on sea ice changes with the constant FSD, suggesting the indirect influences of ocean waves on sea ice through the atmosphere and the ocean.

Carbonaceous aerosols constitute a crucial component of atmospheric marine aerosols among which black carbon (BC) and brown carbon (BrC) are important contributors to light absorption and hence the positive climatic radiative forcing in the marine atmosphere. We conducted month-long (5 May–9 June 2021) onboard sample collections and online measurements of carbonaceous aerosols to characterize their morphological and optical properties during a ship cruise in the South China Sea (SCS), covering a marine region of 11.9–24.5° N, 111.1–118.2° E. Single particles were collected by a single-particle sampler, and offline analyses were performed using a transmission electron microscope (TEM) coupled with energy-dispersive X-ray spectroscopy (EDS). Online measurements of BC in PM2.5 were made by a seven-wavelength aethalometer, and organic carbon (OC) and elemental carbon (EC) mass concentrations were measured by a semi-online OC/EC analyzer. Feret diameters of the single particles during navigation and stop showed size distributions with the lognormal fitting peaks at 307 and 325 nm, respectively. The fresh (without coating) and aged BC particles (after removal of coating by the electron beams in the TEM) showed same median fractal dimensions (1.61), in contrast to their different median lacunarities (0.53 vs. 0.59). The aged BC particles showed narrower Feret diameters (229–2557 nm) during navigation than those (78–2926 nm) of freshly emitted BC from the ship's own exhaust during stop. Moreover, tar balls, as one important component of single particles from ship emissions and as the tracer of biomass burning, were identified with geometrical diameters of 160–420 nm in the TEM images. The EDS analyses showed those tar balls are mainly mixed with sea salt, organics, BC, and sulfate. We also found a significant fraction of aged BC in various mixing states (core–shell, embedded) with other components of the aerosol particles after long-range transport. The campaign was further divided into several periods (the before-monsoon period, BMP; transition monsoon period, TMP; after-monsoon period, AMP; and ship pollution period, SPP) according to the wind direction during monsoon and the ship's own pollution. The median absorption Ångström exponent (AAE) values derived from all wavelengths were 1.14, 1.02, 1.08, and 1.06 for BMP, TMP, AMP, and SPP, respectively. Particularly, a median AAE value of 1.93 was obtained during two significant biomass burning events. These results showed that biomass burning (BB) and fossil fuel (FF) combustion contributed to 18 %–22 % and 78 %–82 % of all the BC light absorption without the two intense biomass burning events, during which BB and FF accounted for 42 % and 58 %, respectively. The two BB events originated from the Philippines and Southeast Asia before and after the summer monsoon. Our results demonstrated that BC can serve as the core of aged particles, but the fractal dimensions of BC aggregates were subject to little variation; moreover, such BC particles become much more aggregated after aging in the marine atmosphere, which further affects the light absorption of the BC particles in the SCS.

Under the influence of climate change, the increasing occurrence of extreme weather events, such as heatwaves, has led to an enhanced frequency of ozone (O3) pollution issues. In August 2022, the Sichuan Basin (SCB), a typical large-scale geographical terrain located in southwestern China, experienced the most severe heatwave in the last 20 years. The heatwave led to substantial disparities in O3 levels across the region. Here, by integrating observations, machine learning, and numerical simulations, we aim to understand the diverse O3 formation mechanisms in two megacities, Chengdu (western location) and Chongqing (eastern location). Observational data showed that Chengdu experienced a consecutive 17 d period of O3 exceedance, in contrast to Chongqing, where O3 concentrations remained below the standard. Meteorological and precursor factors were assessed, highlighting high temperatures, intense solar radiation, and overnight accumulative pollutants as key contributors to O3 concentrations. The interplay of isoprene, temperature, and O3, alongside the observation-based box model and MEGAN simulations, underscored the significant role of intensified biogenic volatile organic compounds (BVOCs) in O3 formation. Interestingly, Chongqing exhibited nearly double the BVOC emissions of Chengdu, yet contributed less to O3 concentrations. This discrepancy was addressed through CMAQ-DDM (Decoupled Direct Method) simulations and satellite diagnosis by investigating the O3–NOx–VOC sensitivity. Notably, Chengdu displayed a VOC-driven sensitivity, while Chongqing showed a transitional regime. Moreover, the regional transport also played a pivotal role in the spatial divergence of O3 pollution. Cross-regional transport predominantly influenced Chongqing (contributing ∼ 80 %), whereas Chengdu was mainly affected by the emissions within the basin. The local accumulated pollutants gave rise to the atmospheric oxidizing capacity, resulting in a substantial photochemical contribution to O3 levels (49.9 ppbv h−1) in Chengdu. This comparison of the difference provides insights into the complex interplay of meteorology, natural emissions, and anthropogenic sources during heatwaves, guiding the necessity of targeted pollution control measures on regional scales.

We report the first measurements of cumulants, up to 4th order, of deuteron number distributions and proton-deuteron correlations in Au+Au collisions recorded by the STAR experiment in phase-I of Beam Energy Scan (BES) program at the Relativistic Heavy Ion Collider. Deuteron cumulants, their ratios, and proton-deuteron mixed cumulants are presented for different collision centralities covering a range of center-of-mass energy per nucleon pair sNN=7.7 to 200 GeV. It is found that the cumulant ratios at lower collision energies favor a canonical ensemble over a grand canonical ensemble in thermal models. An anti-correlation between proton and deuteron multiplicity is observed across all collision energies and centralities, consistent with the expectation from global baryon number conservation. The UrQMD model coupled with a phase-space coalescence mechanism qualitatively reproduces the collision-energy dependence of cumulant ratios and proton-deuteron correlations.

The chiral magnetic effect (CME) is a phenomenon that arises from the QCD anomaly in the presence of an external magnetic field. The experimental search for its evidence has been one of the key goals of the physics program of the Relativistic Heavy-Ion Collider. The STAR Collaboration has previously presented the results of a blind analysis of isobar collisions (_{44}^{96}Ru+_{44}^{96}Ru, _{40}^{96}Zr+_{40}^{96}Zr) in the search for the CME. The isobar ratio (Y) of CME-sensitive observable, charge separation scaled by elliptic anisotropy, is close to but systematically larger than the inverse multiplicity ratio, the naive background baseline. This indicates the potential existence of a CME signal and the presence of remaining nonflow background due to two- and three-particle correlations, which are different between the isobars. In this postblind analysis, we estimate the contributions from those nonflow correlations as a background baseline to Y, utilizing the isobar data as well as Heavy Ion Jet Interaction Generator simulations. This baseline is found consistent with the isobar ratio measurement, and an upper limit of 10% at 95% confidence level is extracted for the CME fraction in the charge separation measurement in isobar collisions at sqrt[s_{NN}]=200 GeV.

The differential cross section for Z0 production, measured as a function of the boson's transverse momentum (pT), provides important constraints on the evolution of the transverse momentum dependent parton distribution functions (TMDs). The transverse single spin asymmetry (TSSA) of the Z0 is sensitive to one of the polarized TMDs, the Sivers function, which is predicted to have the opposite sign in p+p →W/Z+X from that which enters in semi-inclusive deep inelastic scattering. In this Letter, the STAR Collaboration reports the first measurement of the Z0/γ⁎ differential cross section as a function of its pT in p+p collisions at a center-of-mass energy of 510 GeV, together with the Z0/γ⁎ total cross section. We also report the measurement of Z0/γ⁎ TSSA in transversely polarized p+p collisions at 510 GeV.

Water dissolved in nominally anhydrous minerals (NAMs) can be transported to deep regions of the Earth through subducting slabs, thereby significantly influencing the physicochemical properties of deep-Earth materials and impacting dynamic processes in the deep Earth. Stishovite, a prominent mineral present in subducting slabs, remains stable at mantle pressures of 9–50 GPa and can incorporate various amounts of water (H+, OH−, and H2O) in its crystal structure. Consequently, stishovite can play a crucial role in transporting water into the deep Earth through subducting slabs. This paper provides a comprehensive review of the research process concerning water (hydrogen) solubility in stishovite. The key factors that govern water solubility in stishovite are summarized as temperature, pressure, water fugacity, and aluminum content. Combined with published results on the dependence of water solubility on the aforementioned parameters, this paper proposes a new equation to describe the solubility of water in Al-bearing stishovite. Calculation results based on this equation suggest that stishovite may effectively accommodate water released from processes such as hydrous mineral breakdown, which could ultimately contribute to the presence of a water-rich transition zone.

Saline lakes on the Qinghai–Tibet Plateau (QTP) affect the regional climate and water cycle through water loss (E, evaporation under ice-free conditions and sublimation under ice-covered conditions). Due to the observational difficulty over lakes, E and its underlying driving forces are seldom studied when targeting saline lakes on the QTP, particularly during ice-covered periods (ICP). In this study, the E of Qinghai Lake (QHL) and its influencing factors during ice-free periods (IFP) and ICP were first quantified based on 6 years of observations. Subsequently, three models were calibrated and compared in simulating E during the IFP and ICP from 2003 to 2017. The annual E sum of QHL is 768.58±28.73 mm, and the E sum during the ICP reaches 175.22±45.98 mm, accounting for 23 % of the annual E sum. E is mainly controlled by the wind speed, vapor pressure difference, and air pressure during the IFP but is driven by the net radiation, the difference between the air and lake surface temperatures, the wind speed, and the ice coverage during the ICP. The mass transfer model simulates lake E well during the IFP, and the model based on energy achieves a good simulation during the ICP. Moreover, wind speed weakening resulted in an 7.56 % decrease in E during the ICP of 2003–2017. Our results highlight the importance of E in ICP, provide new insights into saline lake E in alpine regions, and can be used as a reference to further improve hydrological models of alpine lakes.

​​​​​​​In the context of non-standard blade geometries of knife-like tools with tapered cutting edges where the width of the blade surface varies with feed, there is limited research on predicting grinding forces considering the changing contact line. To enhance the accuracy of predicting grinding forces during the blade surface grinding of knife-like tools, a novel analytical-regression correction method is proposed. This method employs an analytical approach to analyze the varying contact line between the grinding wheel and the tool during grinding, enabling the determination of irregularly shaped grinding contact zones. By introducing exponential coefficients related to the grinding contact line, a regression analysis is employed to refine a variable edge-width grinding force model. In comparison to the conventional constant contact line blade surface grinding force prediction, this model is better suited for non-standard blade geometries of knife-like tools in grinding processes. Results indicate that the average relative error between the predicted values from the variable edge-width grinding force model and the actual measurements remains within 9 %, thereby validating the model's effectiveness in predicting grinding forces.

The phenomenon of droplets impacting droplets is common in many fields including the chemical, nuclear, and aerospace industries. In this paper, high-speed photography technology is used to obtain the variation law and evolution properties exhibited by droplets colliding with sessile droplets of varying sizes. We further explored how the Weber number (We) and volume ratio (Vp/Vi) influence the behavior of droplets colliding with sessile droplets. The phenomenon of droplets impacting sessile droplets of different volumes is different from that of droplets impacting liquid films. In terms of droplet spreading, compression and the non-splashing liquid crown, the phenomena and laws reported in the present study are applicable for 1 ≤ We ≤ 165 and droplet volume ratios of 1 ≤ Vp/Vi ≤ 6. With a low Weber number, the droplet compresses and deforms downward without coalescence at the initial stage of collision. A high Weber number results in a no-splashing liquid crown. These findings provide important insights into the dynamics of droplet-droplet interactions.

We report results on an elastic cross section measurement in proton–proton collisions at a center-of-mass energy s=510 GeV, obtained with the Roman Pot setup of the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The elastic differential cross section is measured in the four-momentum transfer squared range 0.23≤−t≤0.67 GeV2. This is the only measurement of the proton-proton elastic cross section in this t range for collision energies above the Intersecting Storage Rings (ISR) and below the Large Hadron Collider (LHC) colliders. We find that a constant slope B does not fit the data in the aforementioned t range, and we obtain a much better fit using a second-order polynomial for B(t). This is the first measurement below the LHC energies for which the non-constant behavior B(t) is observed. The t dependence of B is also determined using six subintervals of t in the STAR measured t range, and is in good agreement with the phenomenological models. The measured elastic differential cross section dσ/dt agrees well with the results obtained at s=540 GeV for proton–antiproton collisions by the UA4 experiment. We also determine that the integrated elastic cross section within the STAR t-range is σelfid=462.1±0.9(stat.)±1.1(syst.)±11.6(scale) μb.

The unsteady hypersonic flow under finite amplitude pulse entropy perturbation at different freestream temperatures was calculated by direct numerical simulation. The flow response characteristics under the perturbation of entropy waves in freestreaming are analyzed. The temperature effect of freestreaming is studied based on the sensitivity of the boundary layer caused by pulse entropy perturbation. The results show that the higher freestream temperature promotes the first growth of the above third-order modes after leaving the head region, and strongly inhibits the first attenuation. The influence of the freestream temperature on the evolution of the induced disturbance wave is more significant than that on the development of the main flow disturbance waves. Low freestream temperature can suppress the attenuation of the modes below the second order. As the disturbance wave evolves downstream, the frequency band of the finite frequency disturbance wave gradually narrows, and the frequency band narrows faster when the temperature of freestreaming is low than when the temperature of freestreaming is high.

This paper presents a detection method of DCAM-YOLOv5 for ground penetrating radar (GPR) to address the difficulty of identifying complex and multi-type defects in tunnel linings. The diversity of tunnel-lining defects and the multiple reflections and scattering caused by water-bearing defects make GPR images quite complex. Although existing methods can identify the position of underground defects from B-scans, their classification accuracy is not high. The DCAM-YOLOv5 adopts YOLOv5 as the baseline model and integrates deformable convolution and convolutional block attention module (CBAM) without adding a large number of parameters to improve the adaptive learning ability for irregular geometric shapes and boundary fuzzy defects. In this study, dielectric constant models of tunnel linings are established based on the electromagnetic simulation software (GPRMAX), including rebar and various structural defects. The simulated and field GPR B-scan images show that the DCAM-YOLOv5 method has better results for detecting different types of defects than other methods, which validates the effectiveness of the proposed detection method.

The important roles that the atmospheric boundary layer (ABL) plays in the central Arctic climate system have been recognized, but the atmospheric boundary layer height (ABLH), defined as the layer of continuous turbulence adjacent to the surface, has rarely been investigated. Using a year-round radiosonde dataset during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we improve a Richardson-number-based algorithm that takes cloud effects into consideration and subsequently analyze the characteristics and variability of the ABLH over the Arctic Ocean. The results reveal that the annual cycle is clearly characterized by a distinct peak in May and two respective minima in January and July. This annual variation in the ABLH is primarily controlled by the evolution of the ABL thermal structure. Temperature inversions in the winter and summer are intensified by seasonal radiative cooling and warm-air advection with the surface temperature constrained by melting, respectively, leading to the low ABLH at these times. Meteorological and turbulence variables also play a significant role in ABLH variation, including the near-surface potential temperature gradient, friction velocity, and turbulent kinetic energy (TKE) dissipation rate. In addition, the MOSAiC ABLH is more suppressed than the ABLH during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment in the summer, which indicates that there is large variability in the Arctic ABL structure during the summer melting season.

This paper focuses on VR/AR applications in immovable tangible cultural heritage (ITCH) tourism by considering both academic research and cases in the XR industry. The goal is to understand how VR/AR can be used to present heritage information to the public. A framework is developed, including the purpose of using the technology, hardware, software, and user experience to have an overall understanding of VR/AR applications. Cases collected based on the framework are divided into four heritage types to answer the following questions: under a certain heritage context, what is the commonly used technology, is there a correlation between the purpose of using VR/AR, the enabling technology, and the user experience, and is there a difference in the concentration point between academia and the XR industry in China.

Abstract We report a new measurement of the production of electrons from open heavy-flavor hadron decays (HFEs) at mid-rapidity (|y| < 0.7) in Au+Au collisions at s NN $$ \sqrt{s_{\textrm{NN}}} $$ = 200 GeV. Invariant yields of HFEs are measured for the transverse momentum range of 3.5 < p T < 9 GeV/c in various configurations of the collision geometry. The HFE yields in head-on Au+Au collisions are suppressed by approximately a factor of 2 compared to that in p + p collisions scaled by the average number of binary collisions, indicating strong interactions between heavy quarks and the hot and dense medium created in heavy-ion collisions. Comparison of these results with models provides additional tests of theoretical calculations of heavy quark energy loss in the quark-gluon plasma.

The quantification of large-scale leaf-age-dependent leaf area index has been lacking in tropical and subtropical evergreen broadleaved forests (TEFs), despite the recognized importance of leaf age in influencing leaf photosynthetic capacity in this biome. Here, we simplified the canopy leaves of TEFs into three age cohorts (i.e., young, mature, and old, with different photosynthesis capacities; i.e., Vc,max) and proposed a novel neighbor-based approach to develop the first gridded dataset of a monthly leaf-age-dependent leaf area index (LAI) product (referred to as Lad-LAI) at 0.25∘ spatial resolution over the continental scale during 2001–2018 from satellite observations of sun-induced chlorophyll fluorescence (SIF) that was reconstructed from MODIS and TROPOMI (the TROPOspheric Monitoring Instrument). The new Lad-LAI products show good performance in capturing the seasonality of three LAI cohorts, i.e., young (LAIyoung; the Pearson correlation coefficient of R=0.36), mature (LAImature; R=0.77), and old (LAIold; R=0.59) leaves at eight camera-based observation sites (four in South America, three in subtropical Asia, and one in the Democratic Republic of the Congo (DRC)) and can also represent their interannual dynamics, validated only at the Barro Colorado site, with R being equal to 0.54, 0.64, and 0.49 for LAIyoung, LAImature, and LAIold, respectively. Additionally, the abrupt drops in LAIold are mostly consistent with the seasonal litterfall peaks at 53 in situ measurements across the whole tropical region (R=0.82). The LAI seasonality of young and mature leaves also agrees well with the seasonal dynamics of the enhanced vegetation index (EVI; R=0.61), which is a proxy for photosynthetically effective leaves. Spatially, the gridded Lad-LAI data capture a dry-season green-up of canopy leaves across the wet Amazonian areas, where mean annual precipitation exceeds 2000 mm yr−1, consistent with previous satellite-based analyses. The spatial patterns clustered from the three LAI cohorts also coincide with those clustered from climatic variables over the whole TEF region. Herein, we provide the average seasonality of three LAI cohorts as the main dataset and their time series as a supplementary dataset. These Lad-LAI products are available at https://doi.org/10.6084/m9.figshare.21700955.v4 (Yang et al., 2022).

Instrumental measurements of wind speed and direction from the 1920s to the 1940s from 13 stations in Sweden have been rescued and digitized, making 165 additional station years of wind data available through the Swedish Meteorological and Hydrological Institute's open data portal. These stations measured wind through different versions of cup-type anemometers and were mainly situated at lighthouses along the coasts and at airports. The work followed the protocol “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization consisting of (i) designing a template for digitization, (ii) digitizing records in paper journals by a scanner, (iii) typing numbers of wind speed and direction data into the template, and (iv) performing quality control of the raw observation data. Along with the digitization of the wind observations, meta data from the stations were collected and compiled as support to the following quality control and homogenization of the wind data. The meta data mainly consist of changes in observer and a small number of changes in instrument types and positions. The rescue of these early wind observations can help improve our understanding of long-term wind changes and multidecadal variability (e.g. the “stilling” vs. “reversal” phenomena) but also to evaluate and assess climate simulations of the past. Digitized data can be accessed through the Swedish Meteorological and Hydrological Institute and the following Zenodo repository: https://doi.org/10.5281/zenodo.5850264 (Zhou et al., 2022).

Potential contribution from gamma-ray sources to the Galactic diffuse gamma rays observed above 100 TeV (sub-PeV energy range) by the Tibet AS γ experiment is an important key to interpreting recent multimessenger observations. This paper reveals a surprising fact: none of the 23 Tibet AS γ diffuse gamma-ray events above 398 TeV within the Galactic latitudinal range of ∣ b ∣ < 10° come from the 43 sub-PeV gamma-ray sources reported in the 1LHAASO catalog, which proves that these sources are not the origins of the Tibet AS γ diffuse gamma-ray events. No positional overlap between the Tibet AS γ diffuse gamma-ray events and the sub-PeV LHAASO sources currently supports the diffusive nature of the Tibet AS γ diffuse gamma-ray events, although their potential origin in the gamma-ray sources yet unresolved in the sub-PeV energy range cannot be ruled out.

Density fluctuations near the QCD critical point can be probed via an intermittency analysis in relativistic heavy-ion collisions. We report the first measurement of intermittency in Au+Au collisions at sNN = 7.7-200 GeV measured by the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The scaled factorial moments of identified charged hadrons are analyzed at mid-rapidity and within the transverse momentum phase space. We observe a power-law behavior of scaled factorial moments in Au+Au collisions and a decrease in the extracted scaling exponent (ν) from peripheral to central collisions. The ν is consistent with a constant for different collisions energies in the mid-central (10-40%) collisions. Moreover, the ν in the 0-5% most central Au+Au collisions exhibits a non-monotonic energy dependence that reaches a minimum around sNN = 27 GeV. The physics implications on the QCD phase structure are discussed.

We report on new measurements of elliptic flow (v2) of electrons from heavy-flavor hadron decays at mid-rapidity (|y|

The detuning regulation of a double-pumped microcavity is investigated. In this paper, results show that one of the detuning parameters’ regulation facilitates dual-comb generation. When the other detuning parameter is selected appropriately, dual fields of solitons and Turing patterns generate simultaneously during the detuning. In this case, dual combs with a relatively large repeat frequency difference appear by use of a microcavity. Moreover, properly fast detuning is propitious for stable field evolutions, whereas slow detuning can lead to solitons and Turing patterns drift. Moreover, after the generation of solitons and Turing patterns in the detuning, the method of suddenly stabilizing the detuning parameter to a certain value is used to sustain or regulate the existing fields. When the fixed value of mutation is small, the coexistence of solitons and Turing patterns can be maintained all the time and the large variation value of the detuning parameter results in dual solitons in the microcavity. The results of this paper provide a new approach to excite dual combs taking advantage of a single microcavity.

Abstract Partons traversing the strongly interacting medium produced in heavy-ion collisions are expected to lose energy depending on their color charge and mass. We measure the nuclear modification factors for charm- and bottom-decay electrons, defined as the ratio of yields, divided by the number of binary nucleon–nucleon collisions, in $$\sqrt{s_{\textrm{NN}}}=200$$ s NN = 200 GeV Au+Au collisions to p+p collisions ( $$R_{\textrm{AA}}$$ R AA ), or in central to peripheral Au+Au collisions ( $$R_{\textrm{CP}}$$ R CP ). We find the bottom-decay electron $$R_{\textrm{AA}}$$ R AA and $$R_{\textrm{CP}}$$ R CP to be significantly higher than those of charm-decay electrons. Model calculations including mass-dependent parton energy loss in a strongly coupled medium are consistent with the measured data. These observations provide evidence of mass ordering of charm and bottom quark energy loss when traversing through the strongly coupled medium created in heavy-ion collisions.

This paper presents a new algorithm of the singular value decomposition (SVD) in the wavelet domain for ground penetrating radar (GPR) to remove direct coupled waves. In fact, direct coupled waves commonly disturb the reflecting waves from underground targets. Besides, the amplitude and energy of direct coupled waves are large, which reduces the resolution of the images to the targets and adversely affects the subsequent image interpretation work. The GPR signal is decomposed into several levels by Wavelet to obtain approximation components and detailed components of each level. The information of targets is contained in big eigenvalues of detail components, while the direct coupled waves are contained in small ones. Therefore, the SVD in the wavelet domain can reduce the misjudgment of effective signals and improve the signal to noise ratio (SNR) of GPR signals. The simulated and field GPR data show that the SVD in the wavelet domain denoising method has better results for direct coupled wave removal than the traditional methods, which validates the effectiveness of the proposed denoising method.

The thermal state of permafrost in the present and future is fundamental to ecosystem evolution, hydrological processes, carbon release and infrastructure integrity in cold regions. In 2011, we initiated a permafrost monitoring network along the China–Russia crude oil pipeline (CRCOP) route at the eastern flank of the northern Da Xing'anling Mountains in Northeast China. We compiled an integrated dataset of the ground thermal state along the CRCOP route consisting of meteorological data near the southern limit of latitudinal permafrost, ground temperature (GT) data in 20 boreholes with depths of 10.0–60.6 m, soil volumetric liquid water contents (VWCs) and 2D electrical resistivity tomography (ERT) data at different sites. Results demonstrate a permafrost warming during 2011–2020 in the vicinity of the southern limit of latitudinal permafrost, as manifested by rising GTs at almost all depths in response to climate warming. Local thermal disturbances triggered by the construction and operation of CRCOPs have resulted in significant permafrost warming and subsequent thawing on the right-of-way (ROW) of the pipelines. This permafrost thaw will persist, but it can be alleviated by adopting mitigative measures, such as an insulation layer and thermosyphons. The in situ observational dataset is of great value for assessing the variability of permafrost under the linear disturbances of the CRCOPs and related environmental effects, for understanding hydro–thermal–mechanical interactions between the buried pipelines and permafrost foundation soils, and for evaluating the operational and structural integrity of the pipeline systems in the future. The dataset is available at the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.272357; Li, 2022).

Biomass burning organic aerosol (BBOA) impacts significantly on climate directly through scattering and absorbing solar radiation and indirectly through acting as cloud condensation nuclei. However, fundamental parameters in the simulation of BBOA radiative effects and cloud activities such as size distribution and refractive index remain poorly parameterized in models. In this study, biomass burning events with high combustion efficiency characterized by a high black carbon (BC) to BBOA ratio (0.22 on average) were frequently observed during autumn in the Pearl River Delta region, China. An improved absorption Ångström exponent (AAE) ratio method considering both variations and spectral dependence of black carbon AAE was proposed to differentiate brown carbon (BrC) absorptions from total aerosol absorptions. BBOA size distributions, mass scattering and absorption efficiency were retrieved based on the changes in aerosol number size distribution, scattering coefficients and derived BrC absorptions that occurred with BBOA spikes. Geometric mean diameter of BBOA volume size distribution Dgv depended largely on combustion conditions, ranging from 245 to 505 nm, and a linear relationship between Dgv and ΔBC/ΔBBOA​​​​​​​ was achieved. The retrieved real part of the BBOA refractive index ranges from 1.47 to 1.64, with evidence showing that its variations might depend largely on combustion efficiency, which is rarely investigated in existing literature but which however requires further comprehensive investigations. Retrieved imaginary parts of BBOA refractive index (mi,BBOA) correlated highly with ΔBC/ΔBBOA (R>0.88) but differ a lot from previous parameterization schemes. The reason behind the inconsistency might be that single formula parameterizations of mi,BBOA over the whole BC/BBOA range were used in previous studies which might deviate substantially for specific BC/BBOA ranges. Thus, a new scheme that parameterizes wavelength-dependent mi,BBOA was presented, which filled the gap for field-based BBOA absorptivity parameterizations of ​​​​​​​BC/BBOA >0.1. These findings have significant implications for simulating BBOA climate effects and suggest that linking both BBOA refractive index and BBOA volume size distributions to BC content might be a feasible and a good choice for climate models.

Understanding the hydrological processes related to snow in global mountainous regions under climate change is necessary for achieving regional water and food security (e.g., the United Nation's Sustainable Development Goals 2 and 6). However, the impacts of future snow changes on the hydrological processes in the high mountains of the “Third Pole” are still largely unclear. In this study, we aimed to project future snow changes and their impacts on hydrology in the upstream region of the Salween River (USR) under two shared socioeconomic pathway (SSP) scenarios (SSP126 and SSP585) using a physically based cryosphere–hydrology model. We found that the climate would become warmer (0.2 ∘C per decade under SSP126 and 0.7 ∘C per decade under SSP585) and wetter (5 mm per decade under SPP126 and 27.8 mm per decade under SSP585) in the USR in the future under these two SSPs. In this context, the snowfall, snow cover, snow water equivalent, and snowmelt runoff are projected to exhibit significant decreasing trends during 1995–2100, and the decreases are projected to be most prominent in summer and autumn. The future (2021–2100) snowmelt runoff is projected to significantly increase in spring compared with the reference period (1995–2014), which would benefit the availability of water resources in the growing season. The annual total runoff would significantly increase in all of the future periods due to increased rainfall, which would increase the availability of water resources within the basin, but the high peak flow that occurs in summer may cause rain flooding with short duration and high intensity. Compared with the reference period (the contribution of snowmelt runoff to the total runoff was determined to be 17.5 %), the rain- and snow-dominated pattern of runoff would shift to a rain-dominated pattern after the near term (2021–2040) under SSP585, whereas it would remain largely unchanged under SSP126. Climate change would mainly change the pattern of the snowmelt runoff, but it would not change the annual hydrograph pattern (dominated by increased rainfall). These findings improve our understanding of the responses of cryosphere–hydrological processes under climate change, providing valuable information for integrated water resource management, natural disaster prevention, and ecological environmental protection at the Third Pole.

The physical and heat limits of semiconductor technology require the adaptation of heterogeneous architectures in supercomputers, such as graphics processing units (GPUs) with many-core accelerators and many-core processors with management and computing cores, to maintain a continuous increase in computing performance. The transition from homogeneous multi-core architectures to heterogeneous many-core architectures can produce non-bit-for-bit reproducibility that leads to numerical perturbations and uncertainties in simulation results, which could blend with errors due to coding bugs. The development of a methodology to identify computational perturbations and secure model correctness is a critically important step in model development on computer systems with new architectures. Thus, we have developed a methodology to characterize the uncertainties in the heterogeneous many-core computing environment. This methodology contains a simple multi-column atmospheric model consisting of typical discontinuous physical parameterizations defined by the selection programming structure, an efficient ensemble-based test approach, and an application to the GPU-based high-performance computing (HPC) and Sunway systems. Statistical distributions from ensembles of the heterogeneous systems show quantitative analyses of computational perturbations and acceptable error tolerances. The methodology aims to enable one to fully distinguish between perturbations caused by platforms and discrepancies caused by software bugs, and it provides encouraging references for verifying the reliability of supercomputing platforms and discussing the sensibility of Earth system modeling to the adaptation of new heterogeneous many-core architectures.

The deconfined quark-gluon plasma (QGP) created in relativistic heavy-ion collisions enables the exploration of the fundamental properties of matter under extreme conditions. Noncentral collisions can produce strong magnetic fields on the order of 10^{18} G, which offers a probe into the electrical conductivity of the QGP. In particular, quarks and antiquarks carry opposite charges and receive contrary electromagnetic forces that alter their momenta. This phenomenon can be manifested in the collective motion of final-state particles, specifically in the rapidity-odd directed flow, denoted as v_{1}(y). Here, we present the charge-dependent measurements of dv_{1}/dy near midrapidities for π^{±}, K^{±}, and p(p[over ¯]) in Au+Au and isobar (_{44}^{96}Ru+_{44}^{96}Ru and _{40}^{96}Zr+_{40}^{96}Zr) collisions at sqrt[s_{NN}]=200 GeV, and in Au+Au collisions at 27 GeV, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The combined dependence of the v_{1} signal on collision system, particle species, and collision centrality can be qualitatively and semiquantitatively understood as several effects on constituent quarks. While the results in central events can be explained by the u and d quarks transported from initial-state nuclei, those in peripheral events reveal the impacts of the electromagnetic field on the QGP. Our data put valuable constraints on the electrical conductivity of the QGP in theoretical calculations.

This study investigates present and future European heat wave magnitudes, represented by the Heat Wave Magnitude Index-daily (HWMId), for regional climate models (RCMs) and the driving global climate models (GCMs) over Europe. A subset of the large EURO-CORDEX ensemble is employed to study sources of uncertainties related to the choice of GCMs, RCMs, and their combinations. We initially compare the evaluation runs of the RCMs driven by ERA-interim reanalysis to E-OBS (observation-based estimates), finding that the RCMs can capture most of the observed spatial and temporal features of HWMId. With their higher resolution compared to GCMs, RCMs can reveal spatial features of HWMId associated with small-scale processes (e.g., orographic effects); moreover, RCMs represent large-scale features of HWMId satisfactorily (e.g., by reproducing the general pattern revealed by E-OBS with high values at western coastal regions and low values at the eastern part). Our results indicate a clear added value of the RCMs compared to the driving GCMs. Forced with the emission scenario RCP8.5, all the GCM and RCM simulations consistently project a rise in HWMId at an exponential rate. However, the climate change signals projected by the GCMs are generally attenuated when downscaled by the RCMs, with the spatial pattern also altered. The uncertainty in a simulated future change of heat wave magnitudes following global warming can be attributed almost equally to the difference in model physics (as represented by different RCMs) and to the driving data associated with different GCMs. Regarding the uncertainty associated with RCM choice, a major factor is the different representation of the orographic effects. No consistent spatial pattern in the ensemble spread associated with different GCMs is observed between the RCMs, suggesting GCM uncertainties are transformed by RCMs in a complex manner due to the nonlinear nature of model dynamics and physics. In summary, our results support the use of dynamical downscaling for deriving regional climate realization regarding heat wave magnitudes.

While the formation and evolution of nitrate in airborne particles are extensively investigated, little is known about the processing of nitrate in clouds. Here we present a detailed investigation on the in-cloud formation of nitrate, based on the size-resolved mixing state of nitrate in the individual cloud residual and cloud-free particles obtained by single particle mass spectrometry, and also the mass concentrations of nitrate in the cloud water and PM2.5 at a mountain site (1690 m a.s.l. – above sea level) in southern China. The results show a significant enhancement of nitrate mass fraction and relative intensity of nitrate in the cloud water and the cloud residual particles, respectively, reflecting a critical role of in-cloud processing in the formation of nitrate. We first exclude the gas-phase scavenging of HNO3 and the facilitated activation of nitrate-containing particles as the major contribution for the enhanced nitrate, according to the size distribution of nitrate in individual particles. Based on regression analysis and theoretical calculations, we then highlight the role of N2O5 hydrolysis in the in-cloud formation of nitrate, even during the daytime, attributed to the diminished light in clouds. Nitrate is highly related (R2= ∼ 0.6) to the variations in [NOx][O3], temperature, and droplet surface area in clouds. Accounting for droplet surface area greatly enhances the predictability of the observed nitrate, compared with using [NOx][O3] and temperature. The substantial contribution of N2O5 hydrolysis to nitrate in clouds with diminished light during the daytime can be reproduced by a multiphase chemical box model. Assuming a photolysis rate at 30 % of the default setting, the overall contribution of N2O5 hydrolysis pathway to nitrate formation increases by ∼ 20 % in clouds. Given that N2O5 hydrolysis acts as a major sink of NOx in the atmosphere, further model updates would improve our understanding about the processes contributing to nitrate production in cloud and the cycling of odd nitrogen.

Organic aerosol (OA) has a significant contribution to cloud formation and hence climate change. However, high uncertainties still exist in its impact on global climate, owing to the varying physical properties affected by the complex formation and aging processes. In this study, the hygroscopicity, volatility, cloud condensation nuclei (CCN) activity, and chemical composition of particles were measured using a series of online instruments at a rural site in the Pearl River Delta (PRD) region of China in fall 2019. During the campaign, the average hygroscopicity of OA (κOA) increased from 0.058 at 30 nm to 0.09 at 200 nm, suggesting a higher oxidation state of OA at larger particle sizes, supported by a higher fraction of extremely low volatility OA (ELVOA) for larger size particles. Significantly different diurnal patterns of κOA were observed between Aitken mode particles and accumulation mode particles. For Aitken mode particles (30–100 nm), the κOA values showed daily minima (0.02–0.07) during daytime, while the accumulation mode exhibited a daytime peak (∼ 0.09). Coincidently, a daytime peak was observed for both aged biomass burning organic aerosol (aBBOA) and less oxygenated organic aerosol (LOOA) based on source apportionment, which was attributed to the aging processes and gas–particle partitioning through photochemical reactions. In addition, the fraction of semi-volatile OA (SVOA) was higher at all measured sizes during daytime than during nighttime. These results indicate that the formation of secondary OA (SOA) through gas–particle partitioning can generally occur at all diameters, while the aging processes of pre-existing particles are more dominated in the accumulation mode. Furthermore, we found that applying a fixed κOA value (0.1) could lead to an overestimation of the CCN number concentration (NCCN) up to 12 %–19 % at 0.1 %–0.7 % supersaturation (SS), which was more obvious at higher SS during daytime. Better prediction of NCCN could be achieved by using size-resolved diurnal κOA, which indicates that the size dependence and diurnal variations in κOA can strongly affect the NCCN at different SS values. Our results highlight the need for accurately evaluating the atmospheric evolution of OA at different size ranges and their impact on the physicochemical properties and hence climate effects.

The accumulation of gases into our atmosphere is a growing global concern that requires considerable quantification of the emission rates to mitigate the accumulation of gases in the atmosphere, especially the greenhouse gases (GHGs). In agriculture there are many sources of GHGs that require attention in order to develop practical mitigation strategies. Measuring these GHG sources often relies on highly technical instrumentation originally designed for applications outside of the emissions research in agriculture. Although the open-path laser (OPL) and open-path Fourier transform infrared (OP-FTIR) spectroscopic techniques are used in agricultural research currently, insight into their contributing error to emissions research has not been the focus of these studies. The objective of this study was to assess the applicability and performance (accuracy and precision) of OPL and OP-FTIR spectroscopic techniques for measuring gas mole fractions from agricultural sources. We measured the mole fractions of trace gases methane (CH4), nitrous oxide (N2O), and ammonia (NH3), downwind of point and area sources with a known release rate. The mole fractions measured by OP-FTIR and OPL were also input into models of atmospheric dispersion (WindTrax) allowing the calculation of fluxes. Trace gas release recoveries with WindTrax were examined by comparing the ratio of estimated and known fluxes. The OP-FTIR provided the best performance regarding stability of drift in stable conditions. The CH4 OPL accurately detected the low background (free-air) level of CH4; however, the NH3 OPL was unable to detect the background values ppbv. The dispersion modelling using WindTrax coupled with open-path measurements can be a useful tool to calculate trace gas fluxes from the well-defined source area.

A decisive experimental test of the Chiral Magnetic Effect (CME) is considered one of the major scientific goals at the Relativistic Heavy-Ion Collider (RHIC) towards understanding the nontrivial topological fluctuations of the Quantum Chromodynamics vacuum. In heavy-ion collisions, the CME is expected to result in a charge separation phenomenon across the reaction plane, whose strength could be strongly energy dependent. The previous CME searches have been focused on top RHIC energy collisions. In this Letter, we present a low energy search for the CME in Au+Au collisions at sNN=27 GeV. We measure elliptic flow scaled charge-dependent correlators relative to the event planes that are defined at both mid-rapidity |η|

The linear and mode-coupled contributions to higher-order anisotropic flow are presented for Au+Au collisions at sNN = 27, 39, 54.4, and 200 GeV and compared to similar measurements for Pb+Pb collisions at the Large Hadron Collider (LHC). The coefficients and the flow harmonics' correlations, which characterize the linear and mode-coupled response to the lower-order anisotropies, indicate a beam energy dependence consistent with an influence from the specific shear viscosity (η/s). In contrast, the dimensionless coefficients, mode-coupled response coefficients, and normalized symmetric cumulants are approximately beam-energy independent, consistent with a significant role from initial-state effects. These measurements could provide unique supplemental constraints to (i) distinguish between different initial-state models and (ii) delineate the temperature (T) and baryon chemical potential (μB) dependence of the specific shear viscosity ηs(T,μB).

The roles of microorganisms in enhancing crop production have been demonstrated for a range of cropping systems. Most studies to date, however, have been confined to a limited number of locations, making it difficult to identify general soil biotic and abiotic characteristics underpinning the yield-promotion across various locations. This knowledge gap limits our capacity to harness soil microbiome to improve crop production. Here we used high-throughput amplicon sequencing to investigate the common features of bacterial community composition, ecological networks and physicochemical properties in six yield-invigorating and adjacent yield-debilitating orchards. We found that yield-invigorating soils exhibited higher contents of organic matter than yield-debilitating soils and harbored unique bacterial communities. Greater alpha diversity and higher relative abundances of Planctomycetota and Chloroflexota were observed in yield-debilitating soils. Co-occurrence network analysis revealed that yield-invigorating soils displayed a greater number of functionally interrelated modules (meta-modules) and a higher proportion of negative links to positive links. Chloroflexota was recognized as a keystone taxon in manipulating the interaction of bacterial communities in yield-invigorating soils. Altogether, we provide evidence that yield-invigorating soils across a range of locations appear to share common features, including accumulation of soil organic matter, higher microbial diversity, enrichment of key taxa like Chloroflexota and maintaining a competitive network. These findings have implications for science-based guidance for sustainable food production.

Creating a century-long homogenized near-surface wind speed observation dataset is essential to improve our current knowledge about the uncertainty and causes of wind speed stilling and recovery. Here, we rescued paper-based records of wind speed measurements dating back to the 1920s at 13 stations in Sweden and established a four-step homogenization procedure to generate the first 10-member centennial homogenized wind speed dataset (HomogWS-se) for community use. Results show that about 38 % of the detected change points were confirmed by the known metadata events, and the average segment length split by the change points is ∼11.3 years. Compared with the raw wind speed series, the homogenized series is more continuous and lacks significant non-climatic jumps. The homogenized series presents an initial wind speed stilling and subsequent recovery until the 1990s, whereas the raw series fluctuates with no clear trend before the 1970s. The homogenized series shows a 25 % reduction in the wind speed stilling during 1990–2005 than the raw series, and this reduction is significant when considering the homogenization uncertainty. The homogenized wind speed series exhibits a significantly stronger correlation with the North Atlantic oscillation index than that of the raw series (0.54 vs. 0.29). These results highlight the importance of the century-long homogenized series in increasing our ability to detect and attribute multidecadal variability and changes in wind speed. The proposed homogenization procedure enables other countries or regions to rescue their early climate data and jointly build global long-term high-quality datasets. HomogWS-se is publicly available from the Zenodo repository at https://doi.org/10.5281/zenodo.5850264 (Zhou et al., 2022).