Agglomeration Characteristics Research Articles

Effect of carbon dioxide concentration on the combustion characteristics of boron agglomerates in oxygen-containing atmospheres

Effect of carbon dioxide concentration on the combustion characteristics of boron agglomerates in oxygen-containing atmospheres

Towards a low-carbon society: spatial distribution, characteristics and implications of digital economy and carbon emissions decoupling

Reducing carbon emissions and attaining sustainable economic, social, and environmental development are vital components of the 2030 Agenda for Sustainable Development. Previous research has overlooked the influence of the digital economy on urban carbon decoupling. To bridge this gap, this study employs GIS software and econometric models for analyzing the spatial distribution and characteristics of the digital economy and carbon decoupling and also investigates the direct, heterogeneous, and spatial effects of the digital economy on carbon decoupling. This study reveals: (1) A lesser digital economy presence in the northeast and northwest, while more developed in the Southeast Coast and municipalities directly under the Central Government. Cities with weak carbon decoupling are concentrated in Northeast and North China. (2) The digital economy and the decoupling of urban carbon emissions have spatial correlation and agglomeration characteristics. (3) The digital economy can contribute to decoupling carbon emissions in cities. (4) Improved urban carbon decoupling by the digital economy in central, eastern, and non-resource-based cities. (5) Spatial spillover effect in urban carbon emissions decoupling, yet the digital economy worsens nearby cities’ carbon decoupling due to a siphon effect. That research indicates that the digital economy holds significant promise not only in advancing human progress, bridging the digital divide, and fostering social development but also in driving the decoupling of urban carbon emissions.

Effect of external electric field on agglomeration characteristics of Cu nanoparticles: A molecular dynamics study

In order to study the effect of electric field on the stability of Cu nanoparticles in water, molecular dynamics method was used to simulate the agglomeration characteristics of Cu nanoparticles. The microscopic agglomeration characteristics of nanoparticles by electric field were analyzed using the distribution and collision of nanoparticles in water at different times, as well as the potential energy, kinetic energy, diffusion coefficient and radial distribution function of the system. The results show that the collision of Cu nanoparticles was inhibited in the presence of both uniform and alternation electric fields. The total potential energy of the system decreases with each collision of particles. When all of the particles are agglomerated, the total potential energy of the system remains constant. According to the radial distribution function, when the electric field intensity increases, the degree of aggregation of water molecules on the particle surface strengthens and then weakens as the electric field strength. Meanwhile, the degree of aggregation decreases with the increasing frequency of the alternating electric field. The effect of electric field frequency on the diffusion coefficient of nanofluid is insignificant. However, as the strength of the electric field increases the diffusion coefficient of the nanofluid decreases, while the resistance coefficient of water molecules increases, and the presence of the electric field inhibits the movement of water molecules. The influence of electric field on the heat transfer and deposition characteristics of nanofluids can be obtained by experiments, but the influence mechanism is difficult to be analyzed by experimental means. The molecular dynamics method also provides a new idea to reveal the influence mechanism of electric field.

Thermal behavior and laser-induced heating characteristics of boron agglomerates in various atmospheric conditions

Thermal behavior and laser-induced heating characteristics of boron agglomerates in various atmospheric conditions

Correlation between carbon emissions and water consumption in different industries in China: Spatial and temporal distribution characteristics and driving factors

In order to quantitatively analyze the correlation between carbon emissions and water consumption and identify the main driving factors. Energy consumption and water consumption data of different industries in different provinces of China were collected to calculate the water consumption per unit of carbon dioxide emissions (WCCD) and analyze the characteristics of its spatial and temporal distribution, as well as spatial correlation. The driving factors of WCCD change were quantitatively analyzed by correlation analysis and principal component analysis methods. The results showed that: (1) From 2000 to 2020, WCCD values in each province gradually decreased and approached a plateau. The overall spatial distribution showed more concentration in the south and less in the north, with the North Coastal Economic Zone showing lower values. (2) The spatial correlation of WCCD values is positively correlated, that is, WCCD values have agglomeration characteristics. The WCCD values are mainly ‘high-high aggregation’ and ‘low-low aggregation, which suggests a significant convergence trend and serious polarization. (3) Per capita GDP, per capita energy consumption, and urbanization rate showed an extremely strong correlation with WCCD, while the proportion of the tertiary industry in GDP showed a strong correlation with WCCD. Per capita water resources showed a weak correlation with WCCD. The principal component analysis revealed an increasing impact of economic development on WCCD indicators. This study provides a new perspective for carbon-water relationship research and serves as a fundamental support for water-saving and emission reduction measures.

Mechanism and evolution trend of digital green fusion in China's regional advanced manufacturing industry

This paper has observed pivotal changes in innovative frameworks at the intersection of the digital revolution and sustainable initiatives. Within Industry 4.0, the fusion between intelligent manufacturing and green innovation has become a central driver for sustainability. Integrating these two pivotal forces to harness their collective efficiency is crucial. However, current literature offers limited insights into their combined impact, and the direction of their evolving trends still needs to be defined. Considering this, the research elucidates the core concepts and traits of digital-green fusion (DGF) within regional advanced manufacturing (RAMIDGF). Moreover, this research proposes a double-helix fusion mechanism model. Utilizing data from the advanced manufacturing sectors in six key Chinese urban clusters, this paper adopts a comprehensive analytical toolkit that includes the Coupling Modified Model, Kernel Density Estimation, Markov Chain algorithms, and the Dagum Gini Coefficient for trend analysis. The findings indicate that between 2009 and 2021, RAMIDGF exhibited a trend of initial growth followed by a decline, showing a strong correlation with per capita GDP (RGDP). The principal source of variation in RAMIDGF stems from differences between urban agglomerations, with the Yangtze River Delta and the Beijing-Tianjin-Hebei clusters exhibiting transitional behavior and a ‘ladder-type trend’ in RAMIDGF. As metropolitan clusters become more economically integrated, the probability of transitional behavior in RAMIDGF heightens. However, achieving elevated leapfrog development proves challenging, with an inherent risk of decline. Spatial spillover implications, agglomeration characteristics, and club convergence tendencies mark the RAMIDGF process. These findings expand upon new paradigms for regional sustainable development, offering novel avenues for realizing high-quality growth.

Study on the Spatial Structure of the Complex Network of Population Migration in the Poyang Lake Urban Agglomeration

Population constitutes the foundational element of cities, and population migration drives the transfer of production factors among urban areas. The population migration network serves as an objective representation of intercity interactions, bearing great significance for the analysis of urban network spatial structure. This study focuses on the 10 core cities within the Poyang Lake urban agglomeration. It utilizes population migration data from Tencent’s location-based big data spanning from 2015 to 2018. Employing the point-axis theory from spatial network theory and the directed weighted network theory within the complex network, the study establishes a comprehensive set of network indices and a network model for spatial structure. It investigates the dynamics of population migration networks within the urban agglomeration and considers strategies for enhancing, regulating, or guiding urban agglomeration development to strengthen its overall vitality. The findings indicate that the urban agglomeration displays distinct characteristics of an urban hierarchical sequence and demonstrates gradual improvement in its spatial network development. While network density remains relatively stable across various threshold intervals over an extended period, network connectivity remains weak. Moreover, the urban agglomeration exhibits the lowest degree of centralization, the highest network structure entropy, and limited network connectivity. Migration along the primary power axis within the urban agglomeration remains relatively stable, while the internal network of the urban agglomeration is interconnected through a “core-non-core” network, reflecting near-geographical connection characteristics. Variations in spatial structure are observed, with the spatial network structure following two modes: “weak core city + edge city” and “node city + outer network city”. The trend in network connections diversifies, resulting in both “core-edge” connections and cross-regional connections. In conclusion, the network characteristics of the urban agglomeration surrounding Poyang Lake are consolidated to aid in formulating an optimization plan for the urban agglomeration’s spatial structure. Additionally, these findings serve as a reference for studying the evolution of spatial structures in the other two urban agglomerations within the city agglomeration in the middle reaches of the Yangtze River.

Influence mechanism of dispersion and agglomeration characteristics of micron/nano carbon dust on its combustion kinetics and explosion process

Due to the widespread use of lithium-ion batteries, evaluations of the flammability and explosive characteristics of carbon dust materials as anodes require attention. Carbon dust often reaches the micron/nano scale, and dust particle state and explosion risk generated in different industrial scenarios are different, which is in urgent need of research. Nanoscale dust has relatively static coagulation properties and shows characteristics of dispersion and reagglomeration under a certain airflow. The particle size characteristics affect its thermodynamic characteristics and various consequence parameters of dust explosion. The oxidation and combustion characteristics are mainly affected by dust particle size distribution characteristics. The apparent activation energy is mainly affected by the proportion of small and medium-sized particles and pre-exponential index factor is mainly affected by the dust overall average particle size and specific surface area. The explosion consequence parameters are affected by the thermodynamic parameters, by the disturbance state, particle distribution degree of dust cloud and other factors, which affect the heat radiation and heat transfer process to some extent resulting in different explosion consequence parameters. Due to the agglomeration characteristics of nano-level dust, the minimum ignition energy and minimum ignition temperature of nano-level dust are generally smaller than that of micron level dust.

Controlling the combustion and agglomeration characteristics of solid propellants via new micro-unit composite fuel Al@AP

New micro-unit composite fuels Al@AP with different mass ratios of Al and AP are designed, prepared, and added to solid propellants in place of the original aluminum powder. Through Thermogravimetric Analysis- Differential scanning calorimetry- Mass Spectrometry (TG-DSC-MS), laser ignition experiment, thermocouple temperature measurement, burning rate test, and combustion diagnostic, we study how Al@AP affects the ignition, combustion, and agglomeration properties of solid propellants. The results indicate that the increase of Al content of Al@AP can promote the advance of thermal decomposition of AP. As the AP content increases in Al@AP, the ignition delay time of Al@AP decreases by three times, and the mass burning rate increases by almost five times. At the same time, Al@AP significantly improves the burning rate and temperature gradient. When compare to the baseline propellant, Al@AP-containing propellants present a maximum increase in burning rate of 33% at low pressures and 19% at high pressures. In terms of agglomeration reduction, the number of large-size agglomerates in the CCPs of propellants containing Al@AP is reduced, the average particle size decreases by 78%, and the combustion efficiency increases to 99.34%. A mechanism is proposed to explain how the micro-unit composite fuel Al@AP alters propellant combustion and agglomeration. In summary, Al@AP provides excellent control over ignition, combustion, and agglomeration characteristics. This study provides guidance on the application and development of new aluminum-based composite fuels used in solid propellants.

The Impact of Agricultural Insurance on Urban–Rural Income Gap: Empirical Evidence from China

Based on the panel data of 31 provinces in China from 2005 to 2020, this paper analyzes the mechanism and spatial spillover effect of agricultural insurance on the urban–rural income gap using a fixed effect model, an intermediary effect model, and a two-stage least square method. The results show that agricultural insurance has a significant inhibitory effect on the income gap between urban and rural areas. This inhibitory effect is realized through the path of “improving the development level of agricultural insurance-improving agricultural total factor productivity-reducing the income gap between urban and rural areas”, in which the intermediary effect of agricultural total factor productivity accounts for 19.74% of the total effect. At the same time, the income gap between urban and rural areas in China exhibits typical spatial agglomeration characteristics. The western region has always been the region with the largest income gap between urban and rural areas, while the eastern region is the region with the smallest income gap between urban and rural areas. The development of agricultural insurance has had a spatial spillover effect on the income gap between urban and rural areas, and the development of agricultural insurance in neighboring areas expands the income gap between urban and rural areas in this region. In order to prevent the siphon effect, agricultural insurance investment should be increased in the neighboring regions. The results of this paper support the view of the resource flow model. Finally, we put forward some suggestions for the development of agricultural insurance, improvement in agricultural total factor productivity, and the narrowing of the income gap between urban and rural areas.

Retracted: Research on Spatial Agglomeration Characteristics of Aerospace Cultural and Creative Industries in Smart City under Multidata Fusion

Retracted: Research on Spatial Agglomeration Characteristics of Aerospace Cultural and Creative Industries in Smart City under Multidata Fusion

Spatial and temporal variations of landscape ecological risk in the dry and hot valley of the Jinsha River during 2000-2020

Scientific assessment of landscape ecological risk in ecologically fragile areas of the upper reaches of the Yangtze River is of great significance to regional ecological regulation and construction of the Yangtze River ecological security barrier. With the dry-hot valley area of Jinsha River in Yunnan Province as the research area, we constructed a landscape ecological risk evaluation model, and analyzed the spatial and temporal variations of regional landscape ecological risk. The results showed that the average values of landscape ecological risk index (LER) in the study area were 0.414, 0.398, and 0.462 in 2000, 2010 and 2020, respectively. The LER value of the whole region had reached a higher risk level by 2020. In 2000 and 2010, the landscape ecological risk zones of each level were staggered, and the high-risk zones showed a centralized distribution in 2020. During the two decades, the average LER of each section in the study area was around 0.42, which was close to the high risk level, indicating high landscape ecological risk level. The area of middle and low risk zones had decreased, while the area of high risk zone had significantly increased. The area of high risk zone in the western and middle sections was much higher than that in the eastern section. The area with significant changes of landscape ecological risk accounted for about 55% of the total study area, with obvious spatial agglomeration characteristics of significant increase and decrease of risk. The competition between government-led ecological management policies and measures and market-led land use activities was the main cause of landscape ecological risk variations in this region. In the future, the driving mechanism of climate change coupled with human activities on global and local landscape ecological risk changes in the study area should be uncovered to effectively cope with regional ecological risks.

Research on the spatial-temporal evolution pattern of China's industrial carbon emission efficiency-based on the super-efficiency SBM model

This paper uses the super efficiency SBM model based on unexpected output to calculate the industrial carbon emission efficiency of 30 provinces in China from 2005 to 2019, and uses spatial autocorrelation and other methods to conduct an empirical analysis on the dynamic evolution process and temporal and spatial differences of carbon emission efficiency. The results show that China's industrial carbon emission efficiency is still in the low efficiency stage, with an average value of 0.34. In the study period, although the overall trend is rising, the spatial and temporal differences between provinces are obvious. The overall Moran's I index is subject to the impact of social policy environment on the time path, showing an overall "M" type fluctuation trend, and its spatial difference characteristics change in stages. At the same time, there is a significant global spatial agglomeration effect across the country, and there is a spatial dependency between provinces. The agglomeration trend is significant, forming a cluster with the eastern coastal area as the high value center, and the northwest inland area as the low value center. The Getis OrdGI * index reveals that the local spatial agglomeration characteristics of China's industrial carbon emission efficiency always maintain the pattern of "hot in the east and cold in the west", which echoes the overall spatial evolution pattern of China. The hot spots and sub hot spots of China's industrial carbon emission efficiency are mainly concentrated in the southeast coastal areas with relatively superior economic development, and present a "semi enclosed" pattern. Cold spot area and sub cold spot area gradually evolved into a "suppression" pattern dominated by provinces in northwest China, comprehensively suppressing hot spots. This paper conducts an all-round evaluation of China's industrial carbon emission efficiency from the perspective of regional differentiation, and deeply studies the regional differences and spatial evolution pattern of carbon emission efficien cy in various provinces. It is crucial to achieve the goal of carbon emission reduction in China, and has important practical value and practical significance.

Research on the Distribution Characteristics of Cultivated Land Quality Grades in A County,Liaoning

Cultivated land quality has an important impact on the production capacity of cultivated land and the level of regional development, and is also directly related to national food security. The area-weighted method was used to study the quantity of different cultivated land quality classes in A county, and the spatial autocorrelation analysis was used to study the spatial agglomeration characteristics and differences of cultivated land quality in A county. The results showed that: (1) The natural quality of cultivated land in A county was mainly concentrated in 10-12 grade, while the utilization and economic grades of cultivated land quality were mainly in 11-13 grade, and the utilization and economic qualities of cultivated land were lower than the natural quality. The overall quality of cultivated land in A county was at a medium level. (2) The Moran's I index of natural, utilized and economic quality of cultivated land in A County is greater than 0. 4, showing a strong positive spatial autocorrelation in spatial distribution; In the LISA analysis, the spatial aggregation features of natural, utilized and economic quality of cultivated land turned out to be positive correlated HH type and LL type, and the insignificant NN type distribution was more obvious. (3) Based on the spatial pattern presented by the spatial autocorrelation results, corresponding measures were proposed to provide more scientific references for decision-making and technical support for the implementation of cultivated land fine management in A county.

Migration of spent grain-modified colloidal ferrihydrite: Implications for the in situ stabilization of arsenic, lead, and cadmium in co-contaminated soil

The increase of metal mining, processing, and smelting activities has precipitated a substantial escalation in the contamination of soil by heavy metals. Ferrihydrite (FH) has been commonly used as an amendment for the immobilization of heavy metals in contaminated soil. However, FH suffers from drawbacks such as agglomeration and nonmigratory characteristics, which limit its practical application in soil remediation. Herein, a novel spent grain-modified ferrihydrite (FH-SG) colloidal system was developed, and the FH-SG transport mechanisms in the soil medium were fully studied, focusing in particular on the simultaneous in situ stabilization of arsenic (As), lead (Pb), and cadmium (Cd) in co-contaminated soil. The results showed that the stabilization rates of the FH-SG material reached 94.66%, 96.12%, and 95.52% for water-soluble As, Pb, and Cd, respectively, and 72.22%, 49.39%, and 25.30% for bioavailable As, Pb, and Cd, respectively. The FH-SG material demonstrates notable migration properties in porous media. Theoretical calculation results of a single collector show that the migration deposition of FH-SG material in media is primarily governed by its inherent diffusion characteristics with minimal influence by gravitational forces and media interception. It is noteworthy that the maximum migration distance in quartz sand and soil media with different particle sizes can reach 2.07–2.92 m and 0.78–1.08 m, respectively. Altogether, our findings clearly demonstrate that FH-SG exhibits better stabilization and migration than those of FH alone and most proposed FH colloidal systems. The FH-SG colloidal system holds significant promise for the remediation of various kinds of complex polluted soil.

Spatial Variations and Distribution Patterns of Soil Salinity at the Canal Scale in the Hetao Irrigation District

Soil salinization is a major factor impacting global crop yields. To explore the spatial distribution and influencing factors of soil water and salt in typical canals of the Hetao irrigation district, regional soil information was monitored at fixed locations. In this study, classical statistics, geostatistics, and spatial autocorrelation methods were used to conduct quantitative analyses of soil salt content, water content, soil particle size distribution, and groundwater depth. The variation coefficient of the soil salt content in the 20–40 and 40–60 cm soil layers was between 10% and 100%, which corresponds to a medium degree of variation; the other soil layers had strong degrees of variation. The soil moisture content in each layer varied moderately. The gold coefficients of soil salt content and water content were less than 0.25, and the Z value was greater than 0, showing a strong spatial correlation and certain spatial agglomeration characteristics, which were mainly affected by structural factors in the study area. The distribution patterns of soil water and salt were affected by soil particle size. Sand content decreased with increasing depth, soil salt was negatively correlated with sand content, and soil water was positively correlated with sand content. Soil salinity was significantly affected by groundwater depth and increased with decreasing groundwater depth, following an exponential relationship. When the groundwater depth exceeded 1.7 m, the soil salt content exhibited small changes with groundwater depth. The results of this study could play a guiding role in terms of understanding the degree of soil salinization surrounding canals in the Hetao irrigation area and adjusting land management strategies over time.

Evaluating the sustainability of land use integrating SDGs and its driving factors: A case study of the Yangtze River Delta urban agglomeration, China

Achieving the sustainability of land use (SLU) is of significance in the implementation of the Sustainable Development Goals (SDGs). However, limited research has been conducted on the integrating SDGs into land use assessment. This paper constructs a SLU evaluation framework oriented to SDGs to investigate the spatial-temporal characteristics of SLU during 2000–2020 and its driving factors, taking 192 counties in Yangtze River Delta urban agglomeration (YRD), China as a case. Results show that the SLU level in YRD demonstrates an overall decrease trend of fluctuations, along with obvious regional differences. The spatial pattern of the SLU level in YRD is high in the northern region and low in the southern region, but this gap is gradually narrowing. The spatial distribution of SLU has positive agglomeration characteristics, manifested as HH and L-L types. Furthermore, SLU depends more on the combination of natural and socioeconomic factors. Industrial structure, fiscal deficit, urbanization level, vegetation coverage and precipitation characteristics can promote the SLU, while the economic development level, government intervention and population density have a negative impact on SLU.

Human activities contributing to the accumulation of high-risk trace metal(loid)s in soils of China's five major urban agglomerations

Rapid urbanization has accelerated the accumulation of trace metal(loid)s (TMs) in soils, but the relationship between this accumulation and human activities remains largely unknown. Therefore, based on 775 published literatures (2001–2020), this study aimed to identify the influence of human activities on TM accumulation. Results showed that all soil TM concentrations were higher than their corresponding Chinese soil background values. The pollution risk assessment indicated that the soil TMs in the study area were at moderate levels, and the value of Pollution load index was 2.10. According to the assessment of health risks, the non-carcinogenic risks for adults were at the “Negligible risk” level; while the carcinogenic risk was not negligible for all populations, with children being more susceptible than adults. Meanwhile, six high-risk TMs were identified based on the grading of Contaminating factors (CF ≥ 3) and contribution to health risk (≥ 75%), including four high pollution risk TMs (Cd, Hg, Cu, and Pb) and two high health risk TMs (Cr and As) . In addition, in accordance with the results of the Random forest model, the accumulation of soil high-risk TMs was closely related to influencing factors associated with human activities. The accumulation of Hg and Cr among five major urban agglomerations had the same influencing factors (the number of industrial companies and the amount of industrial wastewater discharge for Hg; the amount of pesticide application and highway mileage for Cr). However, there were significant differences in the factors influencing the accumulation of the other four high-risk TMs (including Cd, As, Cu and Pb), due to the different characteristics of each urban agglomeration. Our results provide new insights into the relationship between human activities and soil TM accumulation.

Identifying the Spatial Patterns and Influencing Factors of Leisure and Tourism in Xi’an Based on Point of Interest (POI) Data

Leisure and tourism spaces are shared by both residents and tourists seeking a higher quality of life. Most of the literature focuses only on the study of a particular type of leisure or tourism space in cities and lacks an overall exploration of the distribution patterns of urban leisure and tourism formats. Based on the leisure and tourism point of interest (POI) data of 11 districts in Xi’an, this paper uses geospatial analysis to examine the spatial patterns of leisure and tourism facilities and their influencing factors in Xi’an. It is found in this study that the distributions overall and the various types of leisure and tourism spaces in Xi’an show the characteristics of central urban agglomeration and sparse dispersion in the surrounding urban areas. Different types of leisure and tourism patterns have obvious spatial scale dependence, but there are differences in the scope of spatial selection. In general, the core agglomeration area has limited radiation and driving effects on the peripheral areas, and there is a prominent phenomenon of imbalance in the distribution of leisure and tourism facilities following a single industrial structure. The formation of the spatial patterns of leisure and tourism is the result of a combination of dominant factors, driving factors, safeguarding factors, and other triggering factors. Urban leisure and tourism spaces are intertwined, and the spatial balance and industrial diversification of leisure and tourism can be promoted through scientific spatial planning. This study aims to provide services for urban land planning and policy-making by revealing the spatial distribution principles of leisure and tourism sites in tourist cities as represented by Xi’an.

A Novel AI Framework for PM Pollution Prediction Applied to a Greek Port City

Particulate matter (PM) pollution is a major global concern due to its negative impact on human health. To effectively address this issue, it is crucial to have a reliable and efficient forecasting system. In this study, we propose a framework for predicting particulate matter concentrations by utilizing publicly available data from low-cost sensors and deep learning. We model the temporal variability through a novel Long Short-Term Memory Neural Network that offers a level of interpretability. The spatial dependence of particulate matter pollution in urban areas is modeled by incorporating characteristics of the urban agglomeration, namely, mean population density and mean floor area ratio. Our approach is general and scalable, as it can be applied to any type of sensor. Moreover, our framework allows for portable sensors, either mounted on vehicles or used by people. We demonstrate its effectiveness through a case study in Greece, where dense urban environments combined with low cost sensor networks is a peculiarity. Specifically, we consider Patras, a Greek port city, where the net PM pollution comes from a variety of sources, including traffic, port activity and domestic heating. Our model achieves a forecasting accuracy comparable to the resolution of the sensors and provides meaningful insights into the results.