Scale Effects Research Articles

Developing an annual global Sub-National scale economic data from 1992 to 2021 using nighttime lights and deep learning

The Gross Domestic Product (GDP) per capita is one of the most widely used socioeconomic indicators, serving as an integral component for climate change impact analysis. However, a national scale assessment may induce considerable bias because it conceals any internal variations within a country. The lack of a long-term sub-national scale GDP data is a substantive hinderance. Leveraging the close relationship between nighttime lights and GDP, we address this gap by developing a novel methodological framework in two steps. First, under the modeling philosophy of spatial statistics, we developed a novel approach based on deep and machine learning techniques to establish a complex mapping between two inconsistent nighttime lights (NTL) datasets: the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP) and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (VIIRS). The models achieve accuracies ranging from 0.945 to 0.980 (correlation coefficients). By taking the estimations ensemble of the two techniques, the time series of DMSP data was extended to 2021. Next, a novel modeling strategy based on multi-layer perceptron was developed to derive the non-linear relationship between NTL and GDP per capita at sub-national scale to alleviate scale effects at this granularity, while explicitly capturing regional heterogeneity effect. The trained models achieve average accuracies of 0.967, 0.959, and 0.959 on the training, validation, and test sets, respectively. We evaluate the developed dataset at the global, national, and sub-national scales from various perspective, and the results offer solid evidence on the reliability of the estimated economic data. By linking to historical global climate change data, we quantify global economic losses attributed to extreme heat to demonstrate how the estimated GDP data can be useful in the climate change impact analysis.

Study on the Scale and Corrosion Inhibition Effect of Curcumin‐Based Novel Polymers

AbstractThe curcumin‐malic acid‐aspartic acid polymer (PCMA) as a new water treatment agent was prepared by solid phase synthesis of curcumin, malic acid and aspartic acid. The static scale inhibition experiments showed that PCMA can inhibit CaCO3 and CaSO4 scale formation by 100.0 % and had excellent scale inhibition effect under various experimental conditions. The mechanism of action of PCMA was obtained by X‐ray diffraction, scanning electron microscope and molecular dynamics simulation. Electrochemical test showed that PCMA is an anodic corrosion inhibitor that achieves 93.1 % corrosion inhibition by forming a protective film on the surface of Q235 carbon steel. Besides, fluorescence spectra proved that PCMA has stable fluorescence intensity.

Simulation study of phonon transport at the GaN/AlN superlattice interface: Ballistic and non-equilibrium phenomena

GaN/AlN superlattice structures have potential for high electron mobility transistors (HEMTs) applications; however, nonequilibrium phonon transport mechanisms within the superlattice have not been systematically investigated. Therefore, we investigate in detail the non-Fourier thermal conductivity of superlattice structures in the perpendicular interface direction and in the parallel interface direction around the phonon BTE numerical solution in this paper, taking the kinetic parameter based on the first principle as the input parameter of the equations and based on the DOM numerical solution scheme. The study reveals that mode temperature non-equilibrium in superlattices arises from ballistic transport within the layers and interface scattering between the layers. The thermal conductivity (TC) of superlattices can be modulated by scale effects, and in superlattices with small thicknesses, phonons exhibit quasi-ballistic transport. The interface thermal resistance predominantly originates from contributions by acoustic phonon (AP) and the first optical phonon (OP1). With increasing interface density, the combined effects of interface scattering and boundary scattering lead to strong phonon scattering, resulting in a decrease in TC parallel to the interfaces. This work provides valuable insights into the thermal transport properties of GaN/AlN superlattice semiconductors and offers useful theoretical guidance for thermal management through phonon particle properties.

Discrete Fracture Network (DFN) as an Effective Tool to Study the Scale Effects of Rock Quality Designation Measurements

Discrete Fracture Network (DFN) as an Effective Tool to Study the Scale Effects of Rock Quality Designation Measurements

Scale effects on core design, fuel costs, and spent fuel volume of pressurized water reactors

The desire to improve the economic competitiveness and deployment pace of nuclear energy through modularization, manufacturing, and series production had led to the development of smaller size reactors. As the standard 17x17 fuel technology is mainly maintained in the pressurized water reactors (PWRs) category, this translates into a lower number of fuel assemblies in the core and sometimes a reduced fuel height. To assess the impact of such scale change in core design on fuel cycle cost and spent fuel volume, a scoping analysis tool is developed based on infinite lattice calculations, leakage, fuel management reduced models, and levelized unit cost of electricity (LCOE) estimate. As such, cost dynamics driven by fuel specific power, burnup, core leakage, feed, cycle length, fuel assembly height as well as uranium market data are captured with consistent set of assumptions and analysis methods. A selection of 5 reactor designs representative of leading PWR developers is assessed and compared. Pursuing higher specific powers and optimal burnups are highlighted as the main fuel cost reduction drivers, nevertheless, practical limitations and opportunities must be evaluated to establish the feasibility of such enhanced fuel operation. In consequence, a detailed core design is performed using SIMULATE3 code for 5 PWR variations including natural and forced coolant circulation modes, two reactor scales, power densities of 73, 112, and 123 kW/l and higher discharge burnups. Design and optimization are performed at the lattice level, for the reflector, and at the core loading level. Satisfactory steady-state operation including power distribution, coolant operating limits, and reactivity requirements are analyzed and reported in this paper. The fuel economics of the detailed core designs confirm the scoping analysis findings. Despite the unlocked power uprates in small PWRs, the achievable burnup for a given fuel specific power requires more enrichment and shorter fuel height results in higher fabrication costs per mass of fuel, which makes scaling down core size a more expensive endeavor on the fuel cycle front. Spent fuel volumes are reported for the PWRs designed in this paper. These volumes are driven by the core average discharge burnup regardless of the scale in consideration. Additional cost and core performance aspects related to heavy reflector gains, fuel-reflector substitution, and disposal cost policy in the U.S. are examined.

Job losses or gains? The impact of supply-side energy transition on employment in China

The supply-side energy transition has created numerous jobs in the renewable energy industry while also destroying jobs in the traditional industry. This study examines the relationship between the supply-side energy transition and employment using panel data from China covering 2008 to 2022. It includes a heterogeneity analysis based on geographical location, economic development, and resource endowments, and estimates net employment based on clean energy production projections. Results show that a 1 % growth in clean energy production led to an approximately 0.013 % increase in total employment. However, that effect was heterogeneous. Employment in the primary industry decreased while the tertiary industry saw an increase. Geographically, employment rose in East and South China but fell in Middle China. Economically, lower-income areas benefited more, which could help reduce talent inequality. Regarding resource endowments, job losses were notable in coal-rich areas and indicated the need for fair transition. Conversely, wind and solar-rich regions experienced higher employment growth, showing a scale effect of clean energy development. By 2060, net employment is projected to increase by 5.89–9.96 million. Policies should be tailored to specific local circumstances in order to also promote a fair, equitable energy transition.

Corrosion Initiation on Reinforcing Steel with Mill Scale in Mortar

Corrosion of reinforcing steel rebar is the main cause of loss of the long-term reliability of concrete structures. When the rebar is corroded, the rust induces cracks and detachment of the cover concrete. The mill scale, a thick oxide film, is formed on the rebars when the rebar is hot rolled. The role of mill scale on the corrosion resistance of rebars in concrete has not been clarified, yet. This study studied the corrosion behavior of rebars with mill scale in mortar.The samples are commercial rebars with 19 mm diameter, which have a mill scale of several tens of micrometers in thickness. The rebars without mill scale prepared by the electrolytic polishing were used as the comparison samples. A Hyperbaric-oxygen accelerated corrosion test (HOACT) [1] was carried out using the rebars embedded in the mortar with a 5.5 mm cover thickness. To prompt the breakdown of passive film on the rebars, 2.1 M NaCl solution was mixed with the mortar. In the HOACT, pressurized oxygen gas is supplied to the sample, and the oxygen reduction reaction on the steel surface is enhanced, leading to the steel's corrosion acceleration. The oxygen pressure was 0.6 MPa and the test period was 14 days. The corrosion of the rebar with a mill scale was more significant than that without a mill scale. This result shows that the mill scale reduces the corrosion resistance of the steel rebar in concrete [2].To investigate the effect of the mill scale on the corrosion resistance of the rebar, anodic polarization measurements of the rebars with and without the mill scale were carried out in a saturated Ca(OH)2 solution containing Cl-. The pitting potential of the rebar with mill scale was more noble than that of the sample without mill scale. However, when the mill scale was scratched, the pitting potential was significantly shifted to the less noble direction, and it was below that of the rebar without the mill scale. These results show that the mill scale improves the corrosion resistance of the rebar in concrete, in contrast, the corrosion resistance of the rebar with a defective mill scale becomes even worse than that of the rebar without the mill scale [2].[1] K. Doi, S. Hiromoto, H. Katayama, E. Akiyama, J. Electrochem. Soc., 165(9), C582-C589 (2018).[2] K. Doi, S. Hiromoto, T. Shinohara, K. Tsuchiya, H. Katayama, E. Akiyama, Corrosion Science, 177, 108995 (2020).

Size-dependent nonlinear free vibration of magneto-electro-elastic nanobeams by incorporating modified couple stress and nonlocal elasticity theory

Magneto-Electro-Elastic (MEE) Composites, as an innovative functional material blend, are composed of multiple materials, boasting exceptional strength, rigidity, and an extraordinary magneto-electric interaction effect. This paper establishes a nonlocal modified couple stress (NL-MCS) magneto-electro-elastic nanobeam dynamic model. To accurately capture the intricate influences of scale effects on nanostructures, This model meticulously examines scale effects from two distinct perspectives: leveraging nonlocal elasticity theory to elucidate the softening phenomena in nanostructures stemming from long-range particle interactions, and employing modified couple stress theory to reveal the hardening effects attributed to the rotational behavior of particles within the structure. By incorporating Von Karman geometric nonlinearity, Reddy’s third-order shear deformation theory and Maxwell’s equations, the governing equations for the nonlinear free vibration of MEE nanobeams are derived using Hamilton’s principle. Finally, a two-step perturbation method is employed to solve these equations. Two-step perturbation method disintegrates the solution process into two stages, iteratively approximating and refining the solution, thereby progressively unraveling the intricate details and enhancing the precision of the solution in a systematic manner. Finally, the nonlinear free vibration behavior of MEE nanobeams is explored under the coupled magnetic-electric-elastic fields, with a focus on the effects of various factors that including length scale parameters, nonlocal parameters, Winkler-Pasternak coefficients, span-to-thickness ratios, applied voltages and magnetic potentials.

Environmental shadows in the age of progress: The toll of economic globalization on China's climate

This study investigates the impact of economic globalization on China's climate using city-level data from 2005 to 2019. This study employs the Spatial Durbin Model (SDM) to reveal an inverted U-shaped relationship between globalization and climate impact, with carbon emissions initially increasing due to scale and composition effects. Surprisingly, the technology effect has limited effectiveness, particularly in second and third-tier cities. Another significant finding of this study is the observed positive correlation between carbon emissions in the previous and current periods. However, this trend leads to lower carbon emissions in neighbouring regions. The results of this study call for technology-focused policies and international collaborations to promote sustainable development in Chinese cities.

Complexity of hydrometeorological variables: false nearest neighbour algorithm

ABSTRACT This study examines the complexity of hydrometeorological variables in the Savitri River basin in India. Specifically, the study estimates the dimensionality of daily rainfall, runoff, maximum temperature, minimum temperature, pan evaporation, relative humidity, sunshine duration, and wind speed observed during 2000–2010 at two stations (Kangule and Birwadi). The false nearest neighbour (FNN) algorithm is employed to estimate the dimensionality of each variable. The dimensionality represents the number of variables dominantly governing the system. The FNN dimension values of the eight daily hydrometeorological time series from each station range between 4 and 7, which may be considered as exhibiting a medium level of complexity. Among the eight series, wind speed is found to be the least complex, whereas minimum temperature and sunshine duration are the most complex. An attempt is also made to examine the effect of temporal scale on the complexity of the hydrometeorological variables, by analysing the hourly rainfall and runoff series from the two stations. The results indicate that, for both rainfall and runoff, hourly data (finer scale) exhibits greater complexity, with two to three additional influential variables. The present results have important implications for hydrometeorological modelling, prediction, and disaster management in the small and flood-prone Savitri River basin.

Scale dependence and mechanisms of grazing‐induced biodiversity changes depend on herbivore type in semiarid grasslands

Abstract Grasslands support a variety of herbivores that profoundly impact biodiversity and ecosystem functioning at local and regional scales. Understanding how different herbivores influence plant diversity across multiple scales is crucial for effective biodiversity conservation. However, most studies have focussed on the effects of grazing intensity on plant diversity, neglecting the impacts and associated mechanisms of different herbivores across scales. Based on a 7‐year grazing experiment with 16 plots in Inner Mongolia's typical steppe, we compared the scale‐dependent effects of different herbivores (cattle, sheep and goats) on plant diversity at moderate grazing intensity. We used the species–area relationship (SAR) and linear mixed models to analyse the changes in species richness across multiple scales (1, 16, 32, 64, 128, 256, 512 and 1024 m2). To understand SAR slope changes, we examined four potential mechanisms: overall species richness, total number of individuals, species abundance distribution and species aggregation. We found that grazing had scale effects on plant diversity, as indicated by a significant decrease in the SAR slope. This decrease in slope suggests that the negative impacts of grazing were more pronounced at larger scales. Additionally, the scale effects of different herbivores on plant diversity varied. Cattle had stronger positive impacts on diversity than sheep and goats at both small (1 m2) and large (1024 m2) scales. Conversely, sheep and goats had stronger negative effects on diversity than did the control at the large scale (1024 m2). The decrease in the SAR slope was mainly caused by changes in overall species richness and species abundance distribution. This was primarily because cattle had a stronger impact on dominant species, whereas sheep and goats had a stronger impact on rare species. Synthesis: Our results demonstrate that even at the same intensity, the grazing effects on species diversity vary with the study scale, herbivore type and their interaction. This finding has important implications for the conservation of grassland biodiversity given that grazing typically occurs at larger scales than in studies with quadrats and involves various herbivores with distinct effects on plant diversity.

Assessment of the influence of roughness, concrete adhesion and scale effect on the shear strength of concrete-gneiss rock interfaces

Assessment of the influence of roughness, concrete adhesion and scale effect on the shear strength of concrete-gneiss rock interfaces

Drivers of industrial carbon emissions in the Yangtze River Delta region, China: A combination of decoupling and LMDI models

ABSTRACT The expansion of the industrial economy has resulted in high carbon emissions (CE) from the Yangtze River Delta (YRD) region. Industrial CE reduction is a non-negligible way to achieve green and low-carbon development. In this paper, we aim to study the decoupling effect of industrial CE and its socio-economic influencing factors in the YRD region from 2005 to 2020. First, the decoupling relationship between industrial CE and industrial output in the YRD region is measured. Then, using the LMDI method, the variation of industrial CE is decomposed into six factors: energy structure ( Δ c s ), energy intensity ( Δ c i ), economic scale ( Δ c e ), labor structure ( Δ c l ), urbanization rate ( Δ c u ) and population size ( Δ c p ) effect. Subsequently, by combining with the decoupling and LMDI models, the contribution of each factor to the decoupling of industrial CE is studied, and the elasticity of each factor is expressed by η s , η i , η e , η l , η u , and η p . The main findings show that: (1) There are two states of weak and strong decoupling between industrial CE and the industrial economy in the YRD. (2) Δ c e is the most powerful factor in promoting industrial CE, while Δ c i and Δ c l are the factors that inhibit industrial CE in the YRD. (3) η i and η l have promoted the decoupling of industrial CE from economic advancement in the YRD and its three provinces and one city, while η e has consistently been the largest obstacle to the decoupling process. Finally, the policy recommendations proposed in this paper aim to help policy-makers and practitioners in the YRD region achieve a win-win balance between industrial CE and industrial output, and inspire further research on the decoupling and decomposition of industrial CE from an academic perspective.

Screen Time Usage and Mental well-being among adolescents: A Cross-Sectional Study

Modern kids are exposed to a wide variety of gadgets and are surrounded by technological advances, including television, cell phones, laptops, and other devices. Young people now spend more time than ever before using electronic gadgets in their daily lives and participating in screen based activities. Aim: This study aims to examine screen time usage, mental well-being and its effect among adolescents. Methods: A cross-sectional study was done among 100 adolescents. Responses were collected by self-structured screen time usage, Warwick-Edinburg Mental well-being scale and self-structured screen time effects scale. Findings: The collected data were analysed by using SPSS version 20.0 and the findings revealed that 42% and 45% of adolescents were using smartphone for 1-3 hours on weekends and weekdays respectively. Forty six percent of adolescents were had low mental well-being. The excessive screen time use reported often feeling moods, headache, frustrated, poor concentration and problem in their eyes. The screen time usage were significantly associated with effects of screen usage (r= 0.27, p=0.04). Conclusion: The study concluded that the adolescents had higher screen time usage on weekends. Increased screen time use predominantly was associated with higher negative effects.

Scale and suction effects on compressibility and time-dependent deformation of mine waste rock material

Designing high mine waste rock piles for long-term behavior requires material mechanical characterization over a large range of stresses and variable environmental conditions. However, representative coarse samples cannot be handled by standard testing devices and the common approach is to test small-scaled samples at the laboratory, which might be affected by particle size effects when compared to the field material. Several reported results indicate that coarser samples present higher amount of particle crushing than small-scaled samples, thus lower dilatancy and higher compressibility. However, specific studies of size effects on time-dependent deformation are lacking. The aim of this paper is to identify the effects of particle size and suction on stress-deformation mechanism of partially saturated mine waste rock. Oedometric compression tests on two parallel graded samples are presented: the gravelly fraction (dmax=50 mm) and the sandy fraction (dmax=2.36 mm). Each stress increment triggers « instantaneous » and delayed strains. The results reveal the combined effects of particle size and humidity on the mechanical behavior. Coarser samples exhibit higher total compressibility and creep deformation, which also increases with the material humidity. The results give empirical support for the development of scaling laws and suggest that total deformation can be decoupled considering a suction dependent index for creep deformation.

Does Scaling Up Pig Farming Promote Carbon Neutrality Among Pig Farmers?

Pig farming is a major source of carbon emissions in China's livestock industry, and the promotion and application of carbon neutral technologies dedicated to carbon reduction and sequestration is a key measure to promote the realization of carbon neutrality in pig farming industry. In the absence of a system for carbon emission reduction in agriculture, it is important to explore whether large-scale pig farming can spontaneously promote the application of carbon neutral technologies by pig farmers. Combined with the technical background of carbon neutrality in pig farming industry and using the field survey data of 468 pig farmers in Shandong Province, this paper empirically analyzed the effect of large-scale pig farming on the carbon neutral behavior of pig farmers. The findings are threefold. Firstly, because of the effect of economies of scale in the application of carbon neutral technologies, large-scale pig farming can promote the carbon neutral behavior of pig farmers. However, the effect of economies of scale in the application of carbon neutral technologies has a boundary, and the annual output of pigs should be maintained at 3000 to 4999. Secondly, among the effects of pig breeding scale on the application and its degree of composting project, state of planting and breeding cycle has no regulating effect. Thirdly, among the effects of pig breeding scale on the application and its degree of biogas engineering, both state of planting and breeding cycle and subsidy for construction of biogas digester have negative regulating effects. In this paper, the pig farming industry is taken as a typical example to reveal the endogenous incentive mechanism of promoting agricultural carbon emission reduction, which provides theoretical reference and experience enlightenment for the formulation of effective policies to promote agricultural carbon neutrality, which are different from industrial industries.

Scale effect of landscape characteristics on undergrowth vegetation variance with different ecological traits

Herbaceous understory vegetation plays a significant role in temperate forested ecosystems, with its diversity strongly dependent on both local and landscape conditions. However, the contribution of these factors across different spatial scales (e.g., scale effect) remains inadequately understood. The objective of this study was to determine the most important landscape and local characteristics influencing the species richness of the herb layer. We surveyed and sampled 53 sites in a mountainous forest within the Baihuashan National Nature Reserve of Beijing. Using generalized linear models, we investigated the simultaneous effect of local (e.g. tree density, average tree height, and cover of tree, shrub, and ground vegetation) and landscape (e.g. Area-weighted Mean Patch Size, Area-weighted Mean Euclidean Nearest Neighbor Distance, Area-weighted Mean Fractal Dimension Index, forest area, and shrubbery area) variables on the richness of species in the understory herb layer. Variation partitioning was used to examine the individual contribution of local and landscape variables. Our results identified 366 plant species from 95 families across 53 sampling sites. Significant differences in species richness were found among life forms, seed dispersal types, and habitat preferences (P < 0.001). Parsimonious models indicated that combining local and landscape factors at a 2 km scale explained the most variation in phanerophytes (R2 = 0.658). Locally, average tree height significantly influenced the species richness of biotic dispersal, phanerophytes, and geophytes. At the landscape level, variables such as the Area-weighted Mean Fractal Dimension Index and farmland area significantly impacted plant community traits across different scales. Understanding these effects is crucial for developing effective sustainable forest ecosystem management strategies and for establishing robust ecological conservation policies.

A complementary approach to quantify the basic GSI chart considering scale effect on rock structure

Geological strength index (GSI) has been widely used as an input parameter in predicting the strength and deformation properties of rock masses. This study derived a series of equations to satisfy the original GSI lines on the basic GSI chart. Two axes ranging from 0 to 100 were employed for surface conditions of the discontinuities and the structure of rock mass, which are independent of the input parameters. The derived equations can analyze GSI values ranging from 0 to 100 within ±5% error. The engineering dimensions (EDs) such as the slope height, tunnel width, and foundation width were used together with representative elementary volume (REV) in jointed rock mass to define scale factor (sf) from 0.2 to 1 in evaluating the rock mass structure including joint pattern. The transformation of GSI into a scale-dependent parameter based on engineering scale addresses a crucial requirement in various engineering applications. The improvements proposed in this study were applied to a real slope which was close to the time of failure. The results of stability assessments show that the new proposals have sufficient capability to define rock mass quality considering EDs.

Effects of wave damping and finite perpendicular scale on three-dimensional Alfvén wave parametric decay in low-beta plasmas

Effects of wave damping and finite perpendicular scale on three-dimensional Alfvén wave parametric decay in low-beta plasmas

Building Shadow Detection Based on Improved Quick Shift Algorithm in GF‐2 Images

Shadows in remote sensing images contain crucial information about various features on the ground. In this study, a method for detecting building shadows in GF‐2 images based on improved quick shift was proposed. First, six feature variables were constructed: first principal component (PC1), brightness component (I), normalized difference shadow index (NDSI), morphological shadow index (MSI), normalized difference water index (NDWI), and normalized difference vegetation index (NDVI). Then, the image was segmented to obtain homogeneous objects, which were then classified using a random forest model. Two improvements were added to the quick shift algorithm: using PC1, I, and MSI as input data instead of RGB images; and adding Canny edge constraints. Validation in six research areas yields Kappa coefficients of 0.928, 0.896, 0.89, 0.913, 0.879, and 0.909, confirming method feasibility. In addition, comparative experiments demonstrate its effectiveness and robustness across different land cover types while mitigating the segmentation scale effect.