Source Region Research Articles

Exploring the future hydropower production of a run-of-river type plant in the source region of the Tigris Basin (Türkiye) under CMIP6 scenarios

This assessment presents a framework for exploring the changing climate impacts on the energy production capacity of a run-of-river type plant, using the Basoren Weir and Hydropower Plant (HPP) as a case study. The Basoren Project is planned considering historical streamflow records in the source region of the Euphrates-Tigris River Basin (ETRB), which is a prominent hotspot warming at nearly double the global average rate. The quantification is built on precipitation and maximum/minimum temperature datasets from 24 Global Climate Models (GCMs) belonging to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) under the moderate- and high-end Shared Socioeconomic Pathway (SSP) scenarios of SSP2-4.5 and SSP5-8.5, as well as the CMIP6 historical experiment (HEXP) scenario. The distribution mapping method is employed to adjust the raw GCM datasets for systematic biases. The Soil and Water Assessment Tool (SWAT) is preferred in producing daily runoff time series for the bias-adjusted simulations of each GCM over the historical (1988-2009) and three future (2025-2049, 2050-2074, and 2075-2099) periods. The ramifications of the changing climate on the Basoren HPP's energy production capacity are assessed based on the medians of the operational results reached for each GCM under the future societal development scenarios of SSP2-4.5 and SSP5-8.5, considering the medians achieved under the HEXP scenario as the reference case. The results indicate potential reductions in the mean yearly energy production of the Basoren HPP by 7.9%, 5.5%, and 5.3% under the SSP2-4.5 scenario, and by 5.8%, 8.0%, and 17.3% under the SSP5-8.5 scenario for the periods 2025-2049, 2050-2074, and 2075-2099, respectively. While declining spillway releases are expected to partly offset the impact of decreasing streamflow rates on energy production, the shift from a snow-dominated to a rain-dominated hydrologic regime necessitates re-optimizing the power capacities of the ETRB plants to maintain effective use of hydropower potential.

Optimizing biomass energy production in the southern region of Iran: A deterministic MCDM and machine learning approach in GIS

This study employs a deterministic approach, distinguishing itself from other renewable energy evaluations, to assess the potential of electrical energy derived from biomass sources in the southern region of Iran. The primary objectives include pinpointing optimal locations for maximal biomass production and subsequent energy generation within distinct climates and topographies, using fuzzy- Analytic Hierarchy Process (AHP). Additionally, Principal Component Analysis (PCA) identify key factors influencing biomass and energy production. The study quantifies electrical and thermal energy derived from biomass sources across various climates. The findings indicate that regions with lower altitudes and humid climates (1530 km2) demonstrate superior biomass performance, leading to increased electrical and thermal energy production. The feature selection process highlights the significant impact of climate and soil characteristics on biomass production and energy output. Analysis of biomass energy production reveals maximum electrical energy production ranging from 674.88 kWh/ha to 711.36 kWh/ha. The results of the Long Short-Term Memory (LSTM) method confirm its high accuracy in estimating electrical energy, with a significant correlation coefficient of 0.98. We conclude that by identifying locations with the best biomass sources based on climate, it is possible to increase the derived electrical energy. These insights are critical for informing energy policies aimed at optimizing biomass energy production and its integration into sustainable power grids.

Large‐Scale Climate Features Control Fire Emissions and Transport in Africa

AbstractRecent increase in extreme wildfire events has led to major health and environmental consequences across the globe. These adverse impacts underlined the need for better understanding of this phenomenon and to formulate mitigating actions. While previous research has focused on local weather drivers of wildfires, our knowledge about their large‐scale climatic controls remains limited, especially in tropical Africa, which stands out as a global hotspot for fire emissions. Here, we show that interannual variability of carbon emission due to fires in the southern Congo Basin is strongly linked to low‐level winds that are controlled by the Indian Ocean subtropical high. The interhemispheric transport of these emissions to West Africa relies on the intensity and position of both Indian and South Atlantic subtropical highs. Combined effects of this transport mechanism and carbon production in the source region explain a majority of the interannual variability of black carbon in West Africa.

High-Efficiency Forward Modeling of Gravitational Fields in Spherical Harmonic Domain with Application to Lunar Topography Correction

Gravity forward modeling as a basic tool has been widely used for topography correction and 3D density inversion. The source region is usually discretized into tesseroids (i.e., spherical prisms) to consider the influence of the curvature of planets in global or large-scale problems. Traditional gravity forward modeling methods in spherical coordinates, including the Taylor expansion and Gaussian–Legendre quadrature, are all based on spatial domains, which mostly have low computational efficiency. This study proposes a high-efficiency forward modeling method of gravitational fields in the spherical harmonic domain, in which the gravity anomalies and gradient tensors can be expressed as spherical harmonic synthesis forms of spherical harmonic coefficients of 3D density distribution. A homogeneous spherical shell model is used to test its effectiveness compared with traditional spatial domain methods. It demonstrates that the computational efficiency of the proposed spherical harmonic domain method is improved by four orders of magnitude with a similar level of computational accuracy compared with the optimized 3D GLQ method. The test also shows that the computational time of the proposed method is not affected by the observation height. Finally, the proposed forward method is applied to the topography correction of the Moon. The results show that the gravity response of the topography obtained with our method is close to that of the optimized 3D GLQ method and is also consistent with previous results.

A novel framework for multiple thermokarst hazards risk assessment and controlling environmental factors analysis on the Qinghai-Tibet Plateau

Due to the influence of climate warming, the degradation of permafrost on the Qinghai-Tibet Plateau (QTP) has become evident. The formation of thermokarst hazards induced by the degradation of ice-rich permafrost has a significant impact on infrastructure construction and local ecology; therefore, it is necessary to assess its risk. Currently, high-precision and harmonized assessment tools for multiple thermokarst hazards risk assessment are lacking, and the mechanisms governing the environmental interactions of thermokarst hazards have not been fully clarified. In this study, a novel multiple thermokarst hazards risk assessment framework was proposed by combining stacking machine learning and potential environmental factors to assess the risk of thermokarst hazards in the Yangtze River source region (YRSR). In addition, model performance was improved by model optimization. Finally, structural equation modeling (SEM) was used to assess the controlling environmental factors for the thermokarst hazards in the YRSR. The results show that slope and precipitation contribute the most to the modeling accuracy of thermokarst lakes and thaw slumps, respectively. Model optimization improved the base model modeling accuracy by approximately 2 % ∼ 7 %, with XGBoost having the highest sensitivity to model optimization and the highest modeling accuracy. In terms of the ensemble strategy, the stacking model and ensemble model significantly improved the risk mapping accuracy, and the stacking model was better than the ensemble model, with accuracies of 92.39 % and 93.36 % for thermokarst lakes and thaw slumps, respectively. Compared with previous results, the results of this study are more representative of the YRSR. Finally, via SEM, terrain factors and soil factors were identified as controlling environmental factors for the risk of thaw slumps and thermokarst lakes, respectively. This study proposes a high-precision risk assessment method for thermokarst hazards in permafrost regions, and contributes to a deeper understanding of the interaction mechanisms between thermokarst hazards and environmental factors.

Regional source contributions to summertime ozone in the Yangtze River Delta

Ozone (O3) pollution is increasing in the Yangtze River Delta (YRD), with significant influences from regional transport during pollution events. However, the specific contributions of different regions remain imprecisely quantified. This study estimated the regional contributions of eight regions to summer O3 in the YRD using the Community Multiscale Air Quality (CMAQ) model with a source-tagged photochemical mechanism. Non-background O3 is attributed to nitrogen oxides (NOX) and volatile organic compounds (VOCs) from different regions. Background O3 is the predominant contributor with average ratios of 75.0%, 65.3%, 64.8% and 63.0% for Shanghai, Nanjing, Hangzhou and the entire YRD, respectively. Locally formed O3 are 39.9, 42.0, 39.6, and 36.9 parts per billion (ppb) by volume in the above areas. North Zhejiang and south Jiangsu are the primary sources of heavy pollution episodes as the maximum daily 8-h average (MDA8) O3 concentrations in these regions increase the most. NOX is the predominant contributor to heavy pollution episodes with the maximum increment attributed to NOX (O3N) of 14.3 ppb, while VOCs only contribute to 2.1 ppb (O3V) in Jiangsu. Relative humidity is crucial in heavy pollution episodes while high temperature, low planetary boundary layer (PBL) height and the wind field are associated with regional transport. Diurnal variation underscores the importance of understanding O3 formation in the afternoon (12:00–16:00), which is essential for devising effective mitigation policies.

Ghost age components in detrital thermochronology

Thermochronological dating of detrital samples is an important tool for understanding the thermal history of basins and their source regions. Detrital thermochronology data are often complex with apparent ages ranging over hundreds of million years due to variations in source-rock cooling age and rate, and the influence of post-depositional burial. A common strategy to interpret such data is to split a dataset into several age components by finite-mixture modeling. Herein, we describe for the first time a remarkable pattern of age components in some thermochronological datasets: two or more components showing ages that are approximately multiples of each other. We apply finite-mixture modeling to a log-normal age distribution (a random effects model) and show that these “ghost age components” are artifacts of inappropriately fitting discrete components to continuous age ranges. The striking pattern of the age components is a direct consequence of the underlying age distribution. For a continuous log-normal age distribution, the ghost components have approximately similar age ratios that depend on the overdispersion and the number of components. Due to their artifactual nature, ghost components appear in a range of dating methods, including fission-track, UPb and (UTh)/He dating, and in equivalent doses of luminescence dating. As they are not geologically meaningful, their occurrence hampers the geological interpretation of thermochronological data. We thus propose to carefully decide for the number of fitted components based on grain properties and additional geological information and to screen modeling results for the constant age ratios that are characteristic of ghost components.

Impacts of the East Asia monsoon on the PM2.5 acidity in Hanoi

This study investigates the acidity of particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) in Hanoi, the capital city of Vietnam, and its influencing factors by analyzing measured concentrations of water-soluble inorganic ions (WSIIs) in 107 24-h samples collected between June 2021 and February 2022. The average sulfate, nitrate, and ammonium concentrations were 5.79, 3.55, and 5.46 μg m−3, respectively. Among the samples, 83 exhibited alkaline aerosols characterized by elevated ammonium-to-sulfate molar concentration ratios (ASMCR) ranging from 2.3 to 9.6, while 24 showed acidic characteristics with ASMCR ranging from 0.5 to 2.5. By employing the Extended Aerosol Inorganic Model E-AIM III, with major WSIIs as the input parameters, the estimated aerosol acidity pH ranged from 8.6 to 10.9 for alkaline aerosols and below 4.5 for acidic aerosols. These variations in ASMCR and aerosol pH highlight the distinct acidic and alkaline aerosol source regions affecting Hanoi's PM2.5 by the monsoon air masses. The Potential Source Contribution Function (PSCF) maps of NH4+ and SO42− revealed the Northeast and Southeast monsoon upwind sources of acidic aerosols over China's Guangdong coastal region and Vietnam's offshore, respectively. Alkaline aerosols were observed during the Northeast and Southwest monsoons, with upwind sources originating in South China, Thailand, and Cambodia. The emergence of the ammonium-rich source areas in South China may be attributed to China's sustained emission control measures, targeting acidic SO2 and NOx emissions while leaving alkaline NH3 emissions largely unaffected. This research provided insights into the intricate relationships between regional emissions, long-range transport, and local meteorological-driven emissions, offering valuable guidance for effective air quality management in urban environments.

Quaternary provenance changes in the loess deposits of the western Chinese Loess Plateau: Insights from U-Pb age spectra of detrital zircon

The western region of the Chinese Loess Plateau (CLP) on the western side of the Liupan Mountains connects the Tibetan Plateau with the deserts of the northern arid zones. This region is key for understanding of the coupled relationship between tectonic uplift and surface processes (erosion and climate) on the Tibetan Plateau; however, the variation of Quaternary wind-dust sources in the region remains uncertain, confounding analysis. In this paper, we conduct a source tracing investigation using detrital zircon U-Pb dating of 12 loess layers from the Huining aeolian sedimentary sequence of the western CLP, reconstruct the history of provenance changes during the Quaternary Period, and further explore driving mechanisms. Results show that aeolian dust from the western CLP is mainly from the northeastern margin of the Tibetan Plateau (NTP). At 1.8–1.66 Ma, the main source region was the NTP, which corresponds to the Episode C uplift event of the Tibetan Plateau. The dominant source area transitioned to the Gobi Altay Mountains (GAMs) around 1.5–1.4 Ma. This shift suggests that the tectonic uplift of the Tibetan Plateau had entered a period of stasis following the conclusion of Episode C, leading to increased transport of detrital material from the GAMs by the East Asian Winter Monsoon. After 1.24 Ma, the dominant source region abruptly changed from the GAMs to the NTP and lasted until 0.04 Ma. The topographic fluctuations caused by the Kunhuang Movement appears to have been the main reason for the sudden source change. Based on our results and evidence from previous studies, the source changes that occurred during the Quaternary Period were in response to a combination of tectonic events and climate change. Comparison of zircon age spectra between the eastern and western CLP further support the idea that the Plateau Winter Monsoon was the main transport system for aeolian dust in the western CLP.

Dependence of ELM instability on separatrix density in EAST long-pulse H-mode plasmas

Abstract The transition from small edge-localized modes (ELMs) to large ELMs has been repetitively observed in minute-scale long-pulse high-confinement mode (H-mode) discharges in 2017 EAST campaign. The appearance of large ELMs is found to be strongly correlated with the decrease in separatrix density due to the gradual decrease in fuel recycling during the long-pulse H-mode operations (LPHOs). By numerical scan of separatrix density with a fixed temperature profile, it has been found that the dependence of ELM instability on separatrix density is related to the competition between the ion diamagnetic stabilizing effect and destabilizing effect of pressure gradient and current density in the pedestal region, shedding light on a comprehensive understanding of different roles of separatrix density in ELM instability observed in EAST experiments. With a high separatrix density, the ideal ballooning mode could be destabilized near the separatrix, which is thought to help achieve small ELMs in EAST LPHOs. In 2021 EAST campaign, the experiment of large ELMs control has been performed through actively changing fuel recycling by moving strike point location (SPL) on the lower tungsten divertor target plate. It has been demonstrated that the mitigation of large ELMs is strongly correlated with the significant increase in separatrix density, which is thought to be attributed to a higher ionization source in the scrape-off layer (SOL) region by SOLPS-ITER simulation. The high ionization source in the SOL region is believed to provide a strong fueling effect near the separatrix and thus raise the local density, which is considered as an important reason for triggering ballooning instabilities near the separatrix and achieving small ELMs.

An evaluation of evapotranspiration products over the Tibetan Plateau

Abstract In situ observations from 13 sites located over the Tibetan Plateau (TP) are used to evaluate evapotranspiration (ET) products, including remote sensing-based, land surface modeled, and reanalysis products. It is found that the Global Land Surface Satellite (GLASS) product, the Global Land Evaporation Amsterdam Model (GLEAM) product, and the simulations by the Community Land Model - Dynamic Global Vegetation Model (CLM-BGCDV) are the top-rank products measured by the Percentage bias, Root Mean Square Error, and Correlation Coefficient against in-situ observations. The evaluated data are then used to examine the consistency in spatial and temporal variability of summer ET and its controlling factors on the TP and the Three-River Sources Region (TRSR). All products show consistently that precipitation in central semiarid part of TP is the dominant factor influencing summer ET, while air temperature plays a certain role in the southeastern and eastern TP. Uncertainties exist in western TP, possibly due to the lack of observations or gaps in the satellite data. Some suggestions for improving ET product development based on models and satellite retrievals, particularly for the cold and complex surface of the TP are also given.

Evaluation and Ranking of Energy Alternatives for Implementation in Different Geographic Scenarios using Decision Methods: Case Study of Colombia

In this research, several crucial aspects have been explored in the evaluation and ranking of energy alternatives in Colombia using advanced decision methods such as TOPSIS and Diffuse TOPSIS. The study analyzed how these techniques allow to effectively compare different renewable energy sources in various regions of the country, highlighting the importance of considering multiple approaches due to the unique geographical and energy characteristics of each region. Specifically, five regions were evaluated: Caribbean 1 and 2, Pacific 1 and 2, Andean, Amazonian and Orinoquia, observing significant differences in the evaluation of technologies between the models. In the evaluation of energy sources for each region, the potential of photovoltaic solar energy in the Caribbean and Orinoquia regions was emphasized due to the high solar radiation, wind energy in the Caribbean and Pacific regions due to its strong winds, and biomass in the Amazon and Andean regions thanks to the abundance of organic resources. These technologies not only contribute to the reduction of carbon emissions and the diversification of the energy matrix, but also promote a just energy transition by generating employment and improving the quality of life in local communities. The TOPSIS method and its diffuse variant make it possible to weigh criteria with different degrees of importance and manage uncertainty in decision-making, resulting in more precise evaluations adapted to specific contexts. This type of research is vital for decision-making in the Colombian electricity sector, as it provides a solid and replicable methodology for evaluating energy alternatives in an integral way. The results not only contribute to environmental sustainability, but also boost the socio-economic development of the regions, fostering an equitable and fair energy transition.

Simulation and Spatio-Temporal Analysis of Soil Erosion in the Source Region of the Yellow River Using Machine Learning Method

The source region of the Yellow River (SRYR), known as the “Chinese Water Tower”, is currently grappling with severe soil erosion, which jeopardizes the sustainability of its alpine grasslands. Large-scale soil erosion monitoring poses a significant challenge, complicating global efforts to study soil erosion and land cover changes. Moreover, conventional methods for assessing soil erosion do not adequately address the variety of erosion types present in the SRYR. Given these challenges, the objectives of this study were to develop a suitable assessment and prediction model for soil erosion tailored to the SRYR’s needs. By leveraging soil erosion data measured by 137Cs from 521 locations and employing the random forest (RF) algorithm, a new soil erosion model was formulated. Key findings include that: (1) The RF soil erosion model significantly outperformed the revised universal soil loss equation (RUSLE) model and revised wind erosion equation (RWEQ) model, achieving an R2 of 0.52 and an RMSE of 5.88. (2) The RF model indicated that from 2001 to 2020, the SRYR experienced an average annual soil erosion modulus (SEM) of 19.32 t·ha−1·y−1 with an annual total erosion in the SRYR of 225.18 × 106 t·y−1. Spatial analysis revealed that 78.64% of the region suffered low erosion, with erosion intensity declining from northwest to southeast. (3) The annual SEM in the SRYR demonstrated a downward trend from 2001 to 2020, with 83.43% of the study area showing improvement. Based on these findings, measures for soil erosion prevention and control in the SRYR were proposed. Future studies should refine the temporal analysis to better understand the influence of extreme climate events on soil erosion, while leveraging high-resolution data to enhance model accuracy. Insights into the drivers of soil erosion in the SRYR will support more effective policy development.

Experimental study on plasma characteristics in the extraction region of a high-power RF negative ion source based on electrostatic probe

Abstract The plasma characteristics of the extraction region in high-power RF negative ion source have a significant impact on the production and extraction of negative hydrogen ions. This study utilized electrostatic probe to investigate the effect of RF power, source pressure, magnetic filter field and bias voltage on the plasma parameters of the extraction region (without cesium), and also studied the variation of plasma parameters with position and time. The results indicate that as RF power increases, the plasma density in the extraction region significantly rises, but it also leads to an increase in the electron temperature ( T e ) of the extraction region (which increases the loss of negative hydrogen ions); increasing the source pressure can effectively increase the electron density ( N e ) in the extraction region and reduce T e as expected; increasing the magnetic filter field can effectively reduce the T e in the extraction region, but after the plasma grid current exceeds 1900 A, the change in T e is not significant; although increasement of the bias voltage can effectively suppress the N e in the extraction region, it causes T e to rise; moreover, the distribution of plasma parameters in the extraction region is relatively uniform; in addition, the variation of plasma parameters with time is not obvious. These findings not only deepen the understanding of the physical mechanisms of plasma behavior in the extraction region of negative ion sources, but also provide important theoretical and experimental bases for the optimization of high-power RF negative ion sources.

Stanley and Acetolysis: Enhanced Method for Pollen Identification and Geolocation of Cocaine Samples

The concept of palynological assemblage, a set of all identifiable pollen grains and spores, is very useful in geolocation determinations in Forensic Studies. To identify plant genera, palynologists must recognize detailed aspects of apertures, ornamentation and layers on the cell wall. Pollen and spores recovered from higher purity cocaine samples represent an alternative to indicate drug source regions. After following the method established by Stanley in 1992, we added the acetolysis procedure in samples seized by the Civil Police of the State of Sao Paulo, Brazil, in 2017, in order to enhance morphological traits observation and taxonomical identification of different pollen taxa, allowing reliable environmental and geolocation reconstructions.

FS-iTFET: advancing tunnel FET technology with Schottky-inductive source and GAA design

In this paper, we introduce a novel Forkshape nanosheet Inductive Tunnel Field-Effect Transistor (FS-iTFET) featuring a Gate-All-Around structure and a full-line tunneling heterojunction channel. The overlapping gate and source contact regions create a strong and uniform electric field in the channel. Furthermore, the metal–semiconductor Schottky junction in the intrinsic source region induces the required carriers without the need for doping. This innovative design achieves both a steeper subthreshold swing (SS) and a higher ON-state current (ION). Using calibration-based simulations with Sentaurus TCAD, we compare the performance of three newly designed device structures: the conventional Nanosheet Tunnel Field-Effect Transistor (NS-TFET), the Nanosheet Line-tunneling TFET (NS-LTFET), and the proposed FS-iTFET. Simulation results show that, compared to the traditional NS-TFET, the NS-LTFET with its full line-tunneling structure improves the average subthreshold swing (SSAVG) by 19.2%. More significantly, the FS-iTFET, utilizing the Schottky-inductive source, further improves the SSAVG by 49% and achieves a superior ION/IOFF ratio. Additionally, we explore the impact of Trap-Assisted Tunneling on the performance of the three different integrations. The FS-iTFET consistently demonstrates superior performance across various metrics, highlighting its potential in advancing tunnel field-effect transistor technology.

Permafrost thaw and thermokarst in the source region of the Yangtze river in the central Tibetan plateau revealed by radar and optical remote sensing

AbstractThe landscape and landforms in permafrost regions are transforming due to climate change and permafrost thaw. This study uses optical and radar remote sensing, alongside spatial analysis, to examine thermokarst features and their driving factors in the source region of the Yangtze River (SRYR) on the central Tibetan Plateau. We analyse the distribution, interaction, and key environmental factors influencing thermokarst ponds and ground surface deformation, which are the two widespread and noticeable thermokarst features. Since the 1960s, the number of small water bodies has doubled from approximately ~2 × 104 to ~4 × 104 by the 2020s, with the median size of these water bodies decreasing from 2.3 × 104 m2 to 1.4 × 104 m2. The permafrost terrain has an average subsidence rate of 6.8 mm/a. About 50.9% of the SRYR exhibits evident thermokarst features. Surficial geological factors, especially geomorphology and slope, are primary factors in shaping the spatial distributions of thermokarst features. Both seasonal deformation and long‐term subsidence rates are more pronounced in areas with thermokarst ponds. However, once pond coverage exceeds around 5%, the amplifying effect on long‐term subsidence rates and seasonal deformation diminishes. The investigation further reveals that the relationship between seasonal deformation and long‐term subsidence is not strictly linear and that the combined increase in seasonal deformation and long‐term subsidence applies only to areas with seasonal deformation below approximately 20 mm. Beyond this threshold, the long‐term subsidence rate is no longer exacerbated by increased seasonal deformation.

Near-α titanium alloy dwell load-induced deformation twinning to coordinate the deformation mechanism associated with crack initiation

In this study, we identified a specific phenomenon of coordinated deformation of twins in near-α titanium alloys during dwell fatigue (DF). The main crack source regions and internal cracks in the micro-texture region (MTR) and no-MTR samples with inconsistent orientation characteristics were characterized. The results demonstrate that the main cracks in all specimens are aligned with the (0001) basal plane, which is associated with basal slip. Notably, twins are found and confirmed to be involved in the DF crack initiation process in high Al content near-α Ti60 alloys where deformation twins are rare, and tend to nucleate at the DF basal cracks. Further in-situ dwell investigation reveals and proposes that the dislocation pile-up and prismatic-basal (PB) interfacial features between soft/hard grains lead to deformation twin nucleation and growth from hard grain boundaries. Concurrently, the pyramidal 〈c+a〉 dislocation slip is observed to be in concurrent operation with the induced twins. These findings suggest that deformation twins not only coordinate basal grain deformation but also hinder the initiation and propagation of basal cracks caused by basal 〈a〉 slip. Moreover, a high density of pyramidal 〈c+a〉 dislocations within the twin and their dissociation to form basal stacking faults (SFTs) with a specific nanometric spacing make the twinning process accompanied by significant lattice distortions inside the twin. These newly formed nanotwin boundaries and SFTs act as barriers to dislocation motion, enhancing the strength and DF lifetime of near-α Ti60 alloys and effectively reducing the dwell sensitivity of no-MTR alloys. Our findings extend the understanding of the coordinated roles of dislocation slip, twin nucleation and formation of basal SFTs in near-α titanium alloys in dwell fatigue.

The origin of interplanetary switchbacks in reconnection at chromospheric network boundaries

There is renewed interest in heliospheric physics following the recent exploration of the pristine solar wind by the Parker Solar Probe. Magnetic switchback structures are frequently observed in the inner heliosphere, but there are open questions about their origin. Many researchers are investigating the statistical properties of switchbacks and their relationships with wave modes, stream types and solar activity, but the sources of switchbacks remain elusive. Here we report that interplanetary switchbacks originate from magnetic reconnection on the Sun that occurs at chromospheric network boundaries and launch solar jet flows. We link in situ interplanetary measurements and remote-sensing solar observations to establish a connection between interplanetary switchbacks and their solar source region, featuring solar jets, chromospheric network boundaries and photospheric magnetic field evolution. Our findings suggest that joint observations of switchbacks and solar jets provide a better estimate of the contribution of magnetic reconnection to coronal heating and solar wind acceleration.

Impacts of fossil fuel thermophoretic convective heat transfer on climate change with variable viscosity and thermal conductivity

The main aim of the current study is to analyze the impacts of fossil fuel thermophoretic convective heat transfer on climate change with variable viscosity and thermal conductivity. Furthermore, the purpose of the proposed problem is to develop a mathematical model based on three regions: source region (in terms of rectangular coordinates), plume region (in terms of cylindrical coordinates), and atmospheric region (in terms of spherical coordinates). The fossil fuels release thermophoretic particles, such as carbon dioxide, methane, black carbon, and many others, during burning process in the source region, and then release through the plume region. These particles are then distributed into the atmosphere, where the impact of thermophoretic particles on climate change is analyzed. The modeled nonlinear partial differential equations are transformed into a dimensionless form using suitable non-dimensional scaling variables. The proposed model is solved using finite difference approach in order to analyze the impacts of fossil fuel thermophoretic particles in the atmosphere in terms of climate change. In this regard, the effect of dimensionless parameters, viscosity variation parameter γ, Schimdt number Sc, thermal conductivity variation parameter ε, coefficient of thermophoretic process k, and thermophoresis parameter Nt on the velocity, temperature, and thermophoretic concentration fields are discussed. The main novelty of current work is that three models in three regions are coupled via trans-boundaries in term of temperature differences. It is very interesting to note that the concentration of thermophoretic particles, along with temperature profile, is maximum at α=π rad and minimum at α=1.5 rad in the atmospheric region.