Vertical Speed Research Articles

Stable Boundary Layers in an Arctic Fjord‐Valley System: Evaluation of Temperature Profiles Observed From Fiber‐Optic Distributed Sensing and Comparison to Numerical Weather Prediction Systems at Different Resolutions

AbstractStable boundary layers (SBLs) commonly form during the Arctic polar night, but their correct representation poses a major challenge for numerical weather prediction (NWP) systems. To enable detailed model verification, we performed measurements of the lower atmospheric boundary layer with airborne fiber‐optic distributed sensing (FODS), a tethered sonde and ground‐based eddy‐covariance (EC) measurements during contrasting synoptic forcings in a fjord‐valley system in Svalbard. The FODS‐derived temperature variances and static stability profiles are used to investigate the spatial and temporal evolution of different inversion types. The strong gradients of the inversions are accompanied by an increased temperature variance, which is related to enhanced buoyancy fluctuations. The observed vertical temperature and wind speed profiles are compared to two configurations of the HARMONIE‐AROME system with different horizontal resolutions at 2.5 and 0.5 km. The higher‐resolution model captures cold pool and low level jet formation during weak synoptic forcing, resulting in a well‐represented vertical temperature profile, while the coarser model exhibits a warm bias in near‐surface temperatures of up to 8 K due to underestimated inversion strength. During changing background flow, the higher‐resolution model is more sensitive to misrepresented fjord‐scale wind directions and performs less well. The results indicate the importance of the ratio between nominal horizontal model resolution and valley width to represent SBL features. Our results underline the substantial benefit of spatially resolving FODS measurements for model verification studies as well as the importance of model and topography resolution for accurate representation of SBLs in complex terrain.

The optimal control law of the power supplied to the wheeled vehicle in case of curvilinear movement

INTRODUCTION: Highly mobile wheeled vehicles are designed to move on roads and terrain in various road and soil conditions, which is accompanied by frequent and significant changes in traction forces and rolling resistance forces. In this regard, in order to maintain vehicle mobility and ensure low energy costs when performing transport tasks, it is necessary to continuously change the operating mode during movement from completely locked to differential in the case of a mechanical transmission. At the same time, the transmission operating mode selected by the driver is not always rational. Thus, the development of a law for controlling the power supplied to the propulsion system, ensuring minimal energy losses while maintaining vehicle mobility in widely varying road conditions, is an urgent task. PURPOSE OF THE STUDY: Increasing the energy efficiency of highly mobile wheeled vehicles by applying a control law for the power supplied to the propulsion system, adaptive to driving conditions. METHODOLOGY AND METHODS: Increasing the energy efficiency of movement can be achieved by reducing losses due to wheel slipping by controlling the power supplied to the propulsion unit. It is advisable to obtain the control law as a result of solving an optimization problem, where the loss power is chosen as the objective function, and the traction forces developed on each of the wheels are chosen as the varied values. At the same time, in order to maintain the possibility of vehicle movement, it is necessary to take into account that the total traction force on all wheels must be determined by external conditions and provided by the power plant. To solve the optimization problem, the Lagrange multiplier method was used. RESULTS AND SCIENTIFIC NOVELTY: The studies carried out made it possible to obtain in analytical form a unified law of adaptive control of the power supplied to the propulsors, applicable in a wide range of road conditions in both straight and curved motion, providing a close to optimal distribution of moments across the driving wheels of the machine, obtained as a result of numerical optimization. PRACTICAL SIGNIFICANCE: The application of the developed law for controlling the power supplied to the propulsors, based on the use in the process of movement of information only about the longitudinal and vertical forces, rotational speeds and angles of rotation of the wheels (trajectory radius), will improve the efficiency of performing transport tasks when moving a vehicle in continuously changing road conditions due to reducing the load on the driver in terms of controlling differential locks in comparison with a manual transmission both in straight and curved motion.

Thin structure of diurnal variations of the vertical wind speed and direction gradients from minisodar data

Thin structure of diurnal variations of the vertical wind speed and direction gradients from minisodar data

Long-term effectiveness of stand-alone anchored spacer in multilevel anterior cervical discectomy and fusion compared with cage-plate system: a systematic review and meta-analysis.

For anterior cervical discectomy and fusion (ACDF), stand-alone anchored spacers (SAAS) and cage-plate system (CPS) are currently employed. However, controversy remains over the effectiveness and security of these two apparatuses in multilevel ACDF. The aim of this study was to demonstrate the global long-term effectiveness and safety of SAAS versus CPS with multilevel ACDF. We conducted a systematic review of studies comparing SAAS with CPS for multilevel ACDF using four electronic databases. Data from this meta-analysis were analyzed with Stata MP 17.0. A total of nine trials comprising 584 patients were selected for inclusion. SAAS significantly reduced operative time, intraoperative bleeding and the incidence of postoperative dysphagia compared with CPS. The SAAS group exhibited significantly smaller cervical sagittal angle (CSA) and fusion segmental height (FSH) compared to CPS group. At final follow-up, the rate of cage sinking was higher in SAAS group compared to CPS group. At the endpoint, there was no difference in JOA score, NDI score, fusion rate or the incidence of adjacent segment degeneration (ASD). SAAS provided comparable long-term effectiveness and safeness for multilevel ACDF regarding JOA scores, NDI scores, fusion rates and ASD rates at endpoint compared to CPS. In comparison to CPS, SAAS demonstrated significant advancement in the reduction of operative time, intraoperative blood loss and the incidence of postoperative dysphagia. As a consequence, SAAS appeared more desirable than CPS among people who needed multilevel ACDF. Yet in long-term observation, SAAS was inferior to CPS in maintaining CSA and FSH and in preventing cage descent. However, whether or not radiographic abnormality has an impact on clinical presentation awaits confirmation from research with more longitudinal follow-up.

Computational Algorithms for Representing Aircraft Instruments with Barometric Physics (Numerical Methods Applied to Flight Simulation)

The present work describes the development of a graphical environment to represent typical flight instruments on a computer screen. The instruments’ behavior is displayed according to information regarding the aircraft’s flight conditions. Some of the instruments represented in this work, such as the altimeter, the vertical speed indicator, the aircraft speed indicator, and the Mach indicator, use air pressure principles. The algorithms and routines developed for the screen display are created using the C++ programming language and compiled independently to be included as libraries to improve the software performance. The algorithms developed for this purpose also include the corresponding relationship between the physical variables, such as the speed and displacement, and the standard atmosphere to provide an equivalent value. These algorithms are successfully tested using data information to simulate three hypothetical flights, which are divided into maneuvers with the aircraft in a stopped position, running on the ground, taking off and flying away, including some changes in directions. Moreover, the routines for displaying the aircraft path with the instruments’ animation are also successfully tested by comparison. Finally, an approach analysis as a function of the step time (Δt) used for calculation of the aircraft displacement to evaluate the efficiency of the numerical method integrated in the simulator is also described. It is proved that the aircraft instrument representation is appropriate according to the input data of the analyzed flights, and an improvement in the calculation can be easily obtained, making it possible to represent any flight condition on the aircraft instruments.

Adhesion of Aluminum Alloy to Tip of Nozzle Plate of Vertical Type High Speed Twin Roll Caster

In a vertical type high-speed twin-roll caster, the adhesion of solidified aluminum alloy to the nozzle (ASAN) makes problems with the quality of the strip surface. The effects of the Si content of Al–Si alloys and the casting conditions on the ASAN were investigated. Alloys with Si contents of 0%, 0.5%, 1%, 2%, 3%, 6% and 10% were considered. The ASAN was high for Si contents of 0.5%, 1%, and 2%. This demonstrates that there is a relationship between the quasi-solid state and the ASAN. As the roll speed and molten metal temperature increased and solidification length decreased, the ASAN decreased. On the basis of these results, the stagnation of molten metal near the nozzle plate was investigated. A gap of 5 mm was introduced between the nozzle plate and the roll surface to eliminate the stagnation of molten metal, resulting in reduction of the ASAN.

Advantages of G-band radar in multi-frequency liquid-phase microphysical retrievals

Abstract. Radar-based microphysical retrievals of cloud and droplet properties are vital for informing model parameterisations of clouds and precipitation, but these retrievals often do not capture the details of small droplets in light rain or drizzle. A state-of-the-art G-band radar is used here to demonstrate improvements to microphysical retrievals in a case study featuring light rain. Compared to W-band radar, improvements are seen in the retrieval of vertical wind speed due to the location of Mie minima at smaller droplet sizes with the G-band radar. This, in turn, has an impact on the retrieval of the drop size distribution, allowing for better accuracy in the retrieval of the characteristic drop diameter and for improvements in the retrieval of the particle number concentrations of small droplet sizes. The dual-Doppler velocity (DDV) between the Ka- and G-bands shows increased dynamic range compared to the Ka–W pairing, particularly for instances presenting small characteristic drop diameters. The increased attenuation experienced at G-band enables improved retrievals of liquid water content and precipitation rate when paired with W-band or Ka-band compared to the W-band and Ka-band pairing. This is particularly noticeable in periods of light rain when the W-band and Ka-band radars receive negligible attenuation, while the attenuation at G-band is much greater.

Approach for the vertical wind speed profile implemented in the UTCI basics blocks UTCI applications at the urban pedestrian level.

The applicability of the Universal Thermal Climate Index (UTCI) at the urban pedestrian level is analysed in relation to the approach for the vertical wind speed profile (VWSP) used in the UTCI basics. As the UTCI refers to the human-biometeorological reference height (zh-b) of 1.1m above ground level (agl), all meteorological input variables for UTCI calculations should also be originated from zh-b. Since the development of the UTCI considered meteorological conventions for stations routinely operated by national weather services, the wind speed (v) as one of four meteorological input variables is initially required at 10m agl (v10 m). In order to calculate v at zh-b from v10 m, the logarithmic law for the VWSP is implemented in the UTCI basics, but only for neutral atmospheric stability and a roughness length (z0) for short-cut grassland (z0 = 0.01m). This methodological approach cannot be changed in the UTCI basics so far. The UTCI developers also recommend the application of the same logarithmic law, if v values at lower heights have to be extrapolated to 10m agl. However, the use of this VWSP approach disregards basic air flow findings and principles in the urban canopy layer (UCL). If the UTCI is nevertheless applied at the urban pedestrian level, inaccuracies in the UTCI values will occur. With reference to z0 = 0.80m, which is more typical for the UCL, they can be up to 7K, as shown in the example of three different climate zones.

Effects of Abelmoschus esculentus leaf as binder in the diet of Oreochromis niloticus fingerlings

Abstract. The experiment was conducted to assess the use of Abelomoschus esculentus leaves soaked for 24 hours as binders in the production of fish feed pellets. Physical properties and dietary effects of the diets were assessed. There was no significant difference (P>0.05) in the sinking rate (cm.sec-1) and bulk density (g/cm3) of experimental diets. There were significant differences (P<0.05) in the thickness strength (mm), water absorption index, hardness (mm) and water stability (%) of experimental diets. Diets MAA and MAW had the highest water stability (88.90±0.46%) while the lowest one was in diet MAI (85.20±0.10%). There was a significant difference (P<0.05) in the friability of experimental diets at different revolution speeds. The highest protein retention was recorded in diet MAI (95.83%) and the lowest one was in diet WHH (91.24%). There was no significant difference (P>0.05) in the mean final weight, mean weight gain, specific growth rate, feed conversion ratio, and feed efficiency of experimental fish-feed experimental diets. Diet MWA had the lowest FCR, the highest FER and SGR. There was a significant difference (P<0.05) in the crude protein, fat, and ash content of carcass of fish fed experimental diets. Fish fed diet MWA had the highest carcass crude protein content (49.27±1.51) and the lowest one was in diet WHE (47.15±0.24). The results showed that A. esculentus leaves can be used as a binder in the production of quality fish feed pellets.

Desert–Oasis Convergence Line and Deep Convection Experiment (DECODE)

Abstract The heterogeneous land surface spanning the Yellow River irrigated oasis and the adjacent Kubuqi and Ulan Buh Desert (Hetao area) in Inner Mongolia, China, has been noted to frequently generate planetary boundary layer convergence line (BLCL), providing an important source of low-level lifting for convection initiation (CI). As the first field experiment to collect comprehensive observations of vegetation-contrast-resulting thermal circulations that consistently generate BLCLs and lead to CI, the Desert–Oasis Convergence Line and Deep Convection Experiment (DECODE) was conducted from 5 July to 9 August 2022 in the Hetao area. Two oasis and four desert observation sites were set up in the region that exhibits the highest frequency of BLCL and CI occurrences, equipped with a suite of advanced instruments probing land–atmosphere interactions, planetary boundary layer processes, and evolution of BLCLs and their associated CI, including Doppler lidars, microwave radiometers, soil temperature and moisture sensors, eddy covariance systems, portable radiosondes, C-band polarimetric Doppler radar, aircraft, and Geostationary High-speed Imager onboard FY-4B satellite. DECODE captured 29 BLCLs (16 with CI), 66 gust fronts, 12 horizontal convective rolls, and one tornado. The observations unveiled full thermal circulations spanning the desert–oasis boundary characterized by a horizontal width of ∼25 km, a convergence height of ∼1 km above ground level (AGL), and divergence from 2 to ∼3.5 km AGL, with vertical wind speeds of up to 2 m s−1. Future publications stemming from DECODE will delve into a spectrum of scientific inquiries, including but not limited to land surface and boundary layer processes, BLCL dynamics, CI mechanisms, convective organization, predictability, and model evaluation.

A Comprehensive Analysis of Optimization Algorithms for Large-Scale Machine Learning

Abstract—Optimization algorithms determine the best model parameters that tend to offer prediction accuracy in complex machine learning (ML) problems in big data. In fact, they are very crucial while handling large-scale data because old ways of handling datasets will be computationally very inefficient. This paper provides an in-depth comparison of the two most widely used optimization techniques in machine learning: SGD, and BGD. Our simulated results indicate that though the SGD technique indicates very fast initial convergence, its efficiency eventually tends to degrade with the increasing iteration of the algorithm. On the other hand, the BGD approach might take slow initiation but is relatively consistent in a long run. We then further probe how the variations in learning rate affect its performance in the case of both the methods. Our analysis shows that adaptive learning rates drastically accelerate convergence. Finally, we show that the computational efficiency of the SGD method makes it a better choice since gradients can be computed on a per sample basis, which makes the method better for scaling. Keywords—Optimization Algorithms, Stochastic gradient de- scent, Batch gradient descent, Machine learning, Large-scale data, and Adaptive learning rate.

Comparison of WP-2 and MOCNESS plankton samplers for measuring zooplankton biomass in the Barents Sea ecosystem.

Zooplankton in the Barents Sea has been monitored on an annual autumn survey since the late 1980s, using vertical WP-2 and oblique Multiple Opening and Closing Net and Environmental Sensing System (MOCNESS) tows over the water column. Sampling with MOCNESS is used to describe thevertical distribution and more frequent sampling with WP-2 (~3:1) to describe the horizontal distribution. We use here a large cumulative data set of 874 MOCNESS and 2850 WP-2 stations with data on size-fractioned dry-weight biomass to compare the two zooplankton sampling gears. MOCNESS is consistently collecting more biomass of the large size fraction (>2mm screen size) by ~20% and less of the small fraction (<1mm) by ~30% compared to WP-2. This is interpreted to reflect more extrusion of small plankton and less avoidance by larger plankton with the MOCNESS. The data set has been collected by three research vessels. There was a difference in vertical speed in oblique tows of MOCNESS among the ships but no clear effect on volume filtered per unit time. This demonstrates operational consistency and suggests theuse of a constant flow factor (distance per flowmeter count) when calculating results over the time series. The issue of calibration of traditional flowmeters on oblique tows needs further examination.

EARLY DETECTION OF BRAIN TUMOR USING MRI AND TRANSFER LEARNING

Brain tumors pose significant risks to cognitive functions, making early detection crucial for improving patient survival rates. Accurate tumor detection aids neuro-oncologists in diagnosing tumor types and recommending appropriate treatments. However, manual detection is challenging, time-consuming, and prone to human error. Recently, Deep Learning (DL) models have demonstrated substantial potential in efficiently classifying large image datasets. This paper presents three novel and efficient multi-class DL architectures leveraging transfer learning to classify different brain tumors. Our primary contribution is to enhance the predictive accuracy while minimizing the usage of computational resource compared to other state-of-art models in the literature by forgoing preprocessing, segmentation, hybrid models, and augmentation techniques. Additionally, we reduce the number of FC layers to streamline computation. We conduct extensive experiments to evaluate the performance of our models using the brain tumor Figshare T1-weighted contrast-enhanced MRI dataset, comprising 3064 images from three distinct tumor types. The InceptionV3 model records a 98.36% accuracy level with five-fold cross-validation. By incorporating batch normalization and optimizing the learning rate for the Adam optimizer, the Xception model reached 99.19% accuracy. Finally, we utilize Particle Swarm Optimization (PSO) to fine-tune the learning rate of the Stochastic Gradient Descent (SGD) optimizer. The Xception model attained 98.85% accuracy. These results highlight the novelty of our approach, offering a practical solution for neuro-oncologists, particularly through the fine-tuned Xception model, which delivers early and accurate tumor detection with minimal computational resources.

Simulated sensitivity of the Amazon rainforest to extreme drought

Abstract The Amazon rainforest is highly biodiverse and the largest intact, tropical forest in the world. Undisturbed tropical forests act as a carbon sink by taking up about 15% of anthropogenic carbon emissions per year. In the past decades, a declining trend in the carbon sink capacity in the Amazon rainforest has been observed due to increased carbon losses and tree mortality. The causes are disputed, but increasing temperatures and more frequent severe droughts are potentially major drivers. We employ a novel modelling framework and hypothesize that previously rare, extreme droughts in the Amazon, such as the ones in 2005 and 2010, constitute the main cause behind the decline of the net carbon sink in aboveground biomass. Our dynamic vegetation model simulates process-based plant hydraulics and drought-induced mortality, and accounts for the diversity of strategies in plant responses to drought based on observed hydraulic vulnerability curves. The simulated impact of the 2005 drought event temporarily turned the annual Amazon net carbon sink to a carbon source of about 0.25 MgC ha-1. In contrast to other dynamic vegetation models our model simulated an increasing trend in carbon losses and a declining trend in the Amazon carbon sink over the past 25 years (net sink rate of -0.018 Mg C ha-1 year-1 or -0.22 Mg C ha-1 per decade) which corresponds well with long-term forest monitoring data (net sink rate of -0.016 Mg C ha-1 year-1). We show that this trend is entirely attributable to drought-induced forest mortality during extreme years. The simulations show a threshold-like behaviour between drought intensity and biomass loss, which is due to xylem vulnerability, indicating the potentially high sensitivity of Amazon forests to extreme drought. Further increases in the severity and frequency of droughts might thus lead to greater carbon release and tree mortality than previously assumed.

FIPEX: Sensor Kinetics of Thin-Film Solid Electrolyte Atomic Oxygen Sensors for Space Applications

Atomic oxygen (AOX) quantification in the upper atmosphere of the Earth is of fundamental interest for the understanding of weather and climate development. Solid electrolyte sensors are suitable instruments for this task since they qualify as payload on all common spaceflight systems due to their small size and low power consumption. The High Enthalpy Flow Diagnostics Group (HEFDiG) at the Institute of Space Systems (IRS) (University of Stuttgart, Germany) has been developing solid electrolyte sensors (FIPEX) for applications aboard sounding rockets in the past 12 years.FIPEX sensors employ YSZ (yttria stabilized zirconia) as solid electrolyte. Together with platinum or gold electrodes they form an electrochemical cell that is operated in an amperometric mode of operation. At elevated temperatures and with a voltage applied between the electrodes this setup forces a migration of oxygen anions through the electrolyte. The corresponding electrical current is measured in an outer circuit and is a function of the AOX flux onto the surface of the sensor.On sounding rockets, the measurement of atomic oxygen is particularly difficult because of the rocket’s high vertical speed yielding strong gradients in AOX number densities along the trajectory. Therefore, our research focuses on the measurement of sensor response times and their reduction. Initially, FIPEX sensors were manufactured with screen printed electrodes that are robust yet comparably thick. Surface diffusion of adsorbed oxygen atoms at the cathode was identified as the rate limiting step in this configuration. In order to reduce the diffusion length, the screen printed electrodes were replaced by porous thin-film electrodes leading to significantly improved response times.This contribution focuses on the analysis of the sensor kinetics governing the behavior of the new thin-film FIPEX sensors. We demonstrate how porosity of the initially dense anode is triggered by high polarization. From this, we provide evidence that an increased porosity at the anode is sufficient to improve the response time of a FIPEX sensor. This is different from the conclusions drawn from the analysis of sensors with thicker screen printed electrodes. An experimental configuration to determine sensor step responses to sufficiently fast changes in oxygen particle flux is presented. Above that, we discuss cyclic voltammetry observations to develop a deeper understanding of the underlying kinetic processes.In conclusion, the transient behavior of thin-film sensors is shown to be dictated by kinetic steps different from what was found for screen printed sensors. Impacts on the suitability and further application of FIPEX sensors in space are presented.Fig. 1: a) Functional layers of a FIPEX sensor. b) Photography of a FIPEX sensor with thin film electrodes. Figure 1

Reconfiguration and compensation design method for single-DoF closed-chain leg mechanism

Compared with a wheeled robot propelled by a rotary drive, a legged robot equipped with multiple motors on a single leg possesses superior adaptability, while at the cost of high energy consumption and less velocity. Inspired by the California mite, the design method of reconfigurable closed-chain leg mechanism with single degree of freedom (DoF) is proposed for effective striding and smooth propelling. Furthermore, the lower-mobility closed-chain leg mechanism is more appropriate for obtaining high frequency and fast movement with the merits of simple control system and rotary drive. Firstly, a reconfigurable design is performed in the swing phase for a high-knee motion intermittently driven by a walking motor through dynamic coupling. Secondly, its fluctuations in vertical displacement and horizontal speed are compensated through the contact outline curve and variable speed input in the supporting phase. Finally, the simulated performance is analyzed and compared, and a prototype is fabricated for fluctuating and obstacle-crossing experiments.

Mechanical carbon emission assessment during prefabricated building deconstruction based on BIM and multi-objective optimization

Machinery operation is a major source of carbon emissions in building deconstruction. Early intervention through Design for Deconstruction (DfD) is crucial for emission reduction, yet the factors influencing these emissions are underexplored. This study integrates parametric BIM with multi-objective optimization (MOO) to assess mechanical carbon emissions in deconstruction. Using the Octopus solver in Grasshopper for Rhino, the study analyzes independent variables—possible working hours (PWH), vertical speed (VS), and horizontal speed (HS)—and dependent variables—minimum mechanical carbon emissions (MCE (min)), minimum deconstruction period (DP (min)), and maximum working efficiency (WE (max)). A lightweight steel roof truss structure is analyzed, comparing real-world deconstruction with optimized DfD schemes. Sensitivity analysis for BIM-MOO optimized results reveal that: (1) Adjusting PWH, VS, and HS significantly affects WE and DP, though with limited impact on carbon emissions; (2) VS influences WE and DP more than HS; (3) Limiting DP is essential for balancing WE, DP, and MCE, with WE adjusted to 20–60% and modifications to PWH and VS achieving balanced management. This study underscores the importance of early design and real-time adjustments for efficient, low-emission deconstruction, supporting the advancement of green building practices.

Modeling of Photodynamic Self-Oscillation Based on a Suspended Liquid Crystal Elastomer Ball System.

Self-oscillation enables continuous motion by transforming constant external stimuli into mechanical work, eliminating the necessity for supplementary control systems. This holds considerable promise in domains like actuators, wearable devices and biomedicine. In the current study, a novel suspended liquid crystal elastomer (LCEs) ball system consisting of a light-responsive hollow LCE ball and an air blower is constructed. Stable illumination allows for its continuous periodic oscillation. Drawing from the theoretical model in conjunction with the dynamic LCE model, the control equations for the system are established, and its dynamic motion characteristics are explored from theoretical viewpoint. The numerical calculations suggest that two motion patterns are present, i.e., hovering and self-oscillatory patterns. The critical conditions required to initiate the transition between two motion patterns are quantified for different system parameters. As evidenced by the outcomes, manipulating the light intensity, damping coefficient, contraction coefficient, air density, gravitational acceleration, bottom illumination zone height, characteristic coefficient and vertical wind speed at the blower outlet facilitates precise control over the motion patterns as well as the amplitude and frequency. With its simple structure, customizable dimensions, remote activation and active manipulation, this system may potentially change the design approach for energy harvesting, microsensors and aerial vehicles.

Enhancing crop yield and carbon sequestration and greenhouse gas emission mitigation through different organic matter input in the Bohai Rim region: An estimation based on the DNDC-RF framework

ContextComprehending the intricacies of crop growth and its impact on greenhouse gas (GHG) emissions is crucial for food security and agricultural resilience to climate change. Research questionAgroecosystem models are instrumental in this endeavor, yet their regional applicability remains constrained. MethodsIn our study, we conducted a rigorous verification of the DNDC (DeNitrification-DeComposition) model across eight representative sites in the Bohai Rim region and determined its efficacy in accurately simulating crop yield, soil organic carbon (SOC), and nitrous oxide (N2O) emissions. We developed a coupled framework, DNDC-RF (DeNitrification-DeComposition-Random Forest), using the RF algorithm in conjunction with DNDC simulation results across fertilization and climate scenarios. Employing the DNDC-RF, we quantitatively evaluated the impact of diverse fertilization strategies on yield and net GHG (including SOC and N2O emissions) under future climate scenarios, spanning the period from 2008 to 2100. ResultsThe DNDC-RF framework accurately predicts SOC, yield, and N2O with high R2 and LCCC, lower RMSE and MAE. Under the RCP4.5 scenario, spring maize yields exhibited a reduction under conventional fertilization measures. However, with organic matters input could achieve the yield increase, particularly additional manure input (9.6 kg C ha−1 yr−1). Summer maize yields were projected to increase under future climate change, with the fastest increase occurring under the RCP8.5 scenario with additional manure input (26 kg C ha−1 yr−1). Wheat yields also increased under future climate change, with the highest growth rate observed with straw return under the RCP8.5 (17.1 kg C ha−1 yr−1). Under different fertilization practices, spring maize fields exhibited a net GHG sink. The best performance was observed with additional manure input and straw return under RCP4.5 and RCP8.5, respectively. In contrast, conventional fertilization in winter wheat-summer maize fields resulted in a net GHG source under both RCP4.5 and RCP8.5. However, the application of organic matter mitigated the net GHG emissions, with additional manure input resulting in the largest increase rate of the net GHG sink. ConclusionsDNDC-RF framework can quickly and effectively solve the difficulties of DNDC model in regional scale prediction (such as complex parameter setting, difficult to accurately and quickly simulate at regional scale and time series), and can accurately simulate regional crop yield, SOC change and N2O emission. With the input of organic matter, the projected yields of maize and wheat are expected to increase, and the field’s ability to act as a net GHG sink could be enhanced. SignificanceOur findings have important scientific significance and practical value for promoting the sustainable development of regional agriculture and formulating effective regional agricultural management measures.

Fouling behavior heterogeneity of typical nanoplastics in widely used polyvinylidene fluoride ultrafiltration membranes

The similarity between the particle size of nanoplastics (NPs) and the pore size of membranes used in water treatment plants may cause overlooked NPs to become potential bothers of membrane processes. Also, various NPs may impact membrane processes differently. Here, fouling behaviors of typical polyvinylidene fluoride ultrafiltration membranes induced by two typical NPs were investigated in environmentally relevant conditions. Results manifested adverse effects of diverse NPs on membranes differed. The flux descent rates of diverse NPs feed solutions-fouled membranes ranged from 9 % to 36 % over 2 h at 0.10 MPa in the dead-end filtration system. Polystyrene nanoplastics caused severer membrane fouling and greater cleaning difficulty than polyethylene nanoplastics did, and the fouling and the cleaning difficulty were both exacerbated with divalent cations present. Also, the incipient fouling was the chief driver. The obtained fouling behavior and cleaning efficiency were compared to the interaction energy data calculated by DLVO theory to better understand underlying fouling mechanisms. Significant correlations were observed between them. Overall, our findings demonstrated the negative impact and its heterogeneity of different NPs on membrane processes, elucidated their mechanisms, and provided scientific bases for NPs membrane fouling control.