Natural Factors Research Articles

Elucidate the complex drivers of significant greening on the Loess Plateau from 2000 to 2020

Greening and its drivers in the Loess Plateau of China have been extensively studied, but attributional explorations regarding vegetation restoration in different climatic zones remain unclear. This study quantitatively evaluated greening on the Loess Plateau based on Fraction Vegetation Cover (FVC) calculated by MOD13Q1 dataset, compared FVC in different climatic zones, and explored the relationship between greening and precipitation, evaporation, soil water content (SWC), surface water bodies, and human activities. The study found that FVC on the Loess Plateau increased significantly at a rate of 0.538% yr−1 from 2000 to 2020, resulting in 94% greening. The greening rate was higher in the middle temperate zones (0.557% yr−1) than in the southern temperate zones (0.532% yr−1), but its average FVC was lower. This suggests that the greening rate (0.551% yr−1) is higher within 5 km of water bodies. Cropland (15.26%), grassland (13.66%) and trees (12.57%) had higher FVC increment than other types, while the six-fold increase in urban area is a significant impediment to greening. Additionally, there is a significant positive correlation with FVC when the urban economy exceeds 100 billion. The interaction of natural factors and human activities made the greatest contribution to greening, as calculated by the GeoDetector. It is hypothesized that there is significant potential for greening in the middle temperate zones. However, large-scale tree planting may not have a catalytic effect and could even be counterproductive. To achieve sustainable greening of the Loess Plateau in the future, shrubs and artificial water storage facilities may be key.

Spatial distribution characteristics of soil heavy metals in Sabao Chaqu watershed of Tuotuo river, Qinghai-Tibet Plateau based on geographic detector

The Qinghai-Tibet Plateau belongs to the area of extremely fragile environment and sensitive to human activities. In recent years, more and more human interference has been detected in this area. In this study, 128 surface soil samples were collected from the Sabao Chaqu watershed of the Tuotuo river at the source of the Yangtze River on the Qinghai-Tibet Plateau. The soil pollution status and spatial distribution characteristics of Cd, Hg, As, Cu, Pb, Cr, Zn and Ni were evaluated by soil accumulation index, enrichment factor, pollution index and geographical detector. The results showed that the average contents of As, Cd, Pb and Zn in the study area were 1.2–3.64 times higher than soil background values of Tibet, while the contents of Hg, Cr, Cu and Ni were lower than the background values, while the average content of As was higher than the soil pollution risk screening value (GB15618-2018), and the pollution index showed that As was in a low pollution state, while the other 7 heavy metals were in a safe state. There were significant differences in the spatial distribution of 8 heavy metals and there was a significant correlation with soil properties and distance factors. Factor detection showed that natural factors had the strongest explanatory power to the contents of As, Cd, Cr, Cu and Ni, distance from the lake and soil Sc content had the strongest explanatory power to Hg content, and anthropogenic factors had the strongest explanatory power to Pb content. Interaction detection revealed that the q values of the strongest interaction explanatory power for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 2.81, 4.30, 1.26, 2.47, 2.33, 1.59, 6.37, and 5.08 times higher than their strongest factor detection explanatory power, respectively. The interaction between anthropogenic factors and other factors has an important influence on the spatial differentiation of heavy metals in the study area. Risk detection showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were the highest in the subregions of MgO, TS, Sc, X6, X13, MgO, TN and X4, respectively. Comprehensive study shows that the spatial differentiation of As, Cd, Cr, Cu, Ni and Zn is mainly affected by natural factors, but there are also some anthropogenic factors, the spatial differentiation of Hg is affected by both natural factors and atmospheric deposition, and the spatial distribution characteristics of Pb are mainly affected by anthropogenic factors.

Economies of scale in Saudi Arabia's refining sector: An application of modern econometric models

This paper aims to reveal how the refining industry's inputs in Saudi Arabia affect its output and to forecast refining industry dynamics. The variables used in this paper are the refined petroleum products representing the dependent variable, with natural gas liquids, crude oil, labor, and capital acting as explanatory variables covering the period 1990–2020. The long run cointegration of the variables was observed. An error correction model utilizing the Cobb–Douglas production function framework was performed. Furthermore, this study applied the vector autoregressive model (VAR) and its diagnosis tests, including forecast-error variance decomposition (FEVD) and impulse response functions (IRFs).The results indicate that natural gas liquids and crude oil have a significant influence on the refining industry's output. Although capital and labor are significant determinants of output, they do not contribute significantly to output creation in the refining industry. This might be related to some parts of the capital and human resources being directed toward supporting activities, such as administration, technical support, maintenance, transportation, logistics and assigning third-party contractors to perform the main duties related to the production process. Additionally, the petroleum refining industry requires substantial capital resources for construction and maintenance. Thus, the actual measurement of capital input's influence on output was observed in the long run. The results reveal that the refining industry's variation is influenced by both its own characteristics and that natural gas liquid, crude oil, capital, and labor factors have a significant impact on the accuracy of industry forecasts.This study concludes that Saudi Arabia's petroleum refining industry operates under decreasing returns to scale, while the shocks in the refining industry are influenced and caused by external factors.

A new in situ magnetic method to indicate the source and seasonal diffusion of heavy metal contamination at Qingdao Beach, China

The accumulation of heavy metals from sewage and garbage dumping can seriously impact beach tourism and thus the local economy, but it is difficult to quickly and accurately determine the pollution location and source of heavy metals and clarify their diffusion range. This study investigates a new in situ magnetic testing method to address this issue. (1) The in situ method can be used to effectively and quickly evaluate heavy metal sources and diffusion ranges based on the distribution of κ values. (2) According to chemical experiments, the specific elements polluting a beach can be determined, such as the Cr, Ni, Zn, and Fe pollution of Beach No. 3. (3) Although κ values for assessing heavy metal pollution on different beaches vary, metal pollution occurs when the higher κ value is more than 50 times the lower κ value on the same beach. (4) The κ values vary in different seasons due to the influence of natural factors and urban seasonal sewage policies.

Analysis and Prediction of Urban Surface Transformation Based on Small Baseline Subset Interferometric Synthetic Aperture Radar and Sparrow Search Algorithm-Convolutional Neural Network-Long Short-Term Memory Model.

With the acceleration of urbanisation, urban areas are subject to the combined effects of the accumulation of various natural factors, such as changes in temperature leading to the thermal expansion or contraction of surface materials (rock, soil, etc.) and changes in precipitation and humidity leading to an increase in the self-weight of soil due to the infiltration of water along the cracks or pores in the ground. Therefore, the subsidence of urban areas has now become a serious geological disaster phenomenon. However, the use of traditional neural network prediction models has limitations when examining the causal relationships between time series surface deformation data and multiple influencing factors and when applying multiple influencing factors for predictive analyses. To this end, Sentinel-1A data from March 2017 to February 2023 were used as the data source in this paper, based on time series deformation data acquired using the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. A sparrow search algorithm-convolutional neural network-long short-term memory (SSA-CNN-LSTM) neural network prediction model was built. The six factors of temperature, humidity, precipitation, and ground temperature at three different depths below the surface (5 cm, 10 cm, and 15 cm) were taken as the input of the model, and the surface deformation data were taken as the output of the neural network model. The correlation between the spatial and temporal evolution characteristics of the ground subsidence in urban areas and various influencing factors was analysed using grey correlation analysis, which proved that these six factors contribute to some extent to the deformation of the urban surface. The main urban area of Hohhot City, Inner Mongolia Autonomous Region, was used as the study area. In order to verify the efficacy of this neural network prediction model, the prediction effects of the multilayer perceptron (MLP), backpropagation (BP), and SSA-CNN-LSTM models were compared and analysed, with the values of the correlation coefficients of the feature points of A1, B1, and C1 being in the range of 0.92, 0.83, and 0.93, respectively. The results show that compared with the traditional MLP and BP neural network models, the SSA-CNN-LSTM model achieves a higher performance in predicting time series surface deformation data in urban areas, which provides new ideas and methods for this area of research.

River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion

River ecosystem health assessment (REHA), an effective approach for identifying river ecosystem health, is crucial for achieving sustainable river management and ensuring water security. However, existing REHA methods still fail to consider the cumulated influences of uncertain inputs, stochastic environment and limited rationality of decision makers on REHA. Additionally, current REHA studies have mainly concentrated on plain areas, while the Qinghai-Tibet Plateau (QTP) remains largely unknown. Developing REHA techniques for plateau rivers is an urgent matter, due to the heightened fragility and complexity of river ecosystems in the QTP. To accurately assess river ecosystem health in the QTP, this study proposed Pythagorean fuzzy cloud (PFC) via coupling the Pythagorean fuzzy sets and cloud model. A novel PFC-TODIM model was developed by extending TODIM (the acronym in Portuguese for interactive and multicriteria decision making) to the Pythagorean fuzzy environment. The hybrid decision making framework was then created to handle REHA with uncertain inputs and stochastic environment, and the Senge Tsangpo River (STR) served as a case study in the QTP. We developed the indicator system based on multi-source data fusion, and employed Bayesian model averaging (BMA) method to reveal the potential risks and driving factors of river ecosystem health. Results showed that the developed models considered the limited rationality of decision makers, effectively handled REHA with uncertainties, and avoided overestimating river health levels due to ignoring the randomness and fuzziness of REHA. In STR, health statuses exhibited marked spatial differences. Sampling sites of 9.091%, 77.273 % and 13.636 % were excellent, healthy and subhealthy, respectively. Our findings highlight that dams, urban development, fish release, and grazing have adverse impacts on STR health, and effective protection measures are required to minimize human interferences on ecologically fragile areas. These findings can improve our understanding of the human disturbances and natural factors that interfere with river ecosystem health in the QTP.

Isolated non-immune mediated second-degree atrioventricular block in fetus: natural history and predictive factors for spontaneous recovery.

To uncover the clinical course of fetal isolated non-immune mediated second-degree AVB and determine the factors associated with the spontaneous recovery for fetal non-immune second-degree atrioventricular block (AVB). A total of 20 fetuses with isolated, non-immune mediated second-degree AVB were prospectively recruited between 2014 and 2022. These fetuses were divided into the spontaneous recovery group (n=12) and the non-spontaneous recovery group (n=8). Maternal and fetal basic characteristics, intrauterine and postnatal outcomes were compared between groups. Twelve fetuses restored 1:1 atrioventricular conduction in utero and did not recur during the postnatal follow-up period. The residual eight fetuses maintained as second-degree AVB and six of them were aborted due to parental request in utero. Of the two live children with second-degree AVB, one of them progressed to complete AVB at the latest follow up at the age of 34 months, but without any symptoms, heart enlargement or dysfunction. The residual one progressed to complete AVB and was finally diagnosed with type 2 long-QT syndrome. Fetuses in the spontaneous recovery group presented with earlier gestational age at diagnosis (20.0[17.0-26.0] vs. 24.5[18.0-35.0] weeks, p=0.004) and higher atrial rate (147[130-160] vs 138.00[125.00-149.00] bpm, p=0.006) in comparison with the non-spontaneous recovery group. A cut-off value of 22.5 weeks of gestational age and 144 bpm of atrial rate at diagnosis could predict the failure of spontaneous recovery, with sensitivities of 87.5%, 75%, and specificities of 92.0%, 87.5%, respectively. The outcome of fetal non-immune second-degree AVB was favorable. Earlier gestational age at diagnosis and higher atrial rate were related to spontaneous reversion for isolated non-immune-mediated second-degree AVB. However, prenatal gene test should be performed for those with persistent AVB to exclude the heritable disorders including LQTS. These findings may provide important references for clinical management and prenatal counseling. This article is protected by copyright. All rights reserved.

Adaptation of students' bodies in the fight against stress. Regulating modes for mental health balance

A healthy lifestyle has a wide range of positive effects on various aspects of the human body and personality. In the psychological aspect. The benefits of a healthy lifestyle are manifested as mental health, well-being, neuropsychological stability, the ability to successfully endure the effects of mental stress, and self-confidence. In the functional manifestation, it is possible to note a higher quality of health, improvement of adaptation processes, increase of working capacity and training, reduction of diseases and painful sensations.
 Physical self-education is understood as the process of purposeful, conscious, planned work on oneself and focused on the formation of physical culture of the individual. A personal physical self-education plan should have the following tasks: strengthening health, hardening the body, developing perseverance, training coordination abilities, training endurance, improving physical development and physical readiness in accordance with the requirements of future professional activity.
 It is necessary to use the following means and methods: morning gymnastics, physical exercises, hygienic and natural factors, exercises for the development of coordination, running, hiking, cycling. Based on the results of this plan, you should keep a self-monitoring diary. Systematic filling of the self-monitoring diary is a report on the work done. Thus, the student's ability to note even minor changes in self-improvement is important, as it reinforces his confidence in his abilities, activates, and contributes to the further improvement of the self-education program, the implementation of a healthy lifestyle.

Clinical effectiveness of emollients with 30% urea and antiseptic Dorogov's stimulator in liposomal form in the complex therapy of chronic dermatoses

One of the modern trends in the study of the protective barrier of the skin is the study of the dynamics of the skin process. As a result of the active inflammatory process, a decrease in moisture levels occurs, a violation of the hydrolipid mantle of the skin and a decrease in natural moisturizing factors. The formation and maintenance of a protective skin barrier is an important pathogenetic tool in the treatment of inflammatory dermatoses. Chronic dermatoses often require regular topical therapy, so safe, convenient and effective topical regimens with good cosmetic properties can be very beneficial for this group of patients. Moisturizing and barrier-restoring formulations are clinically recognized as valuable topical treatments for patients with chronic dermatoses.

Integrating meteorological and geospatial data for forest fire risk assessment

Understanding the factors that cause fire is crucial for minimizing the fire risk. In this research, a comprehensive approach was adopted to recognize factors influencing forest fires. Golestan National Park (GNP) was considered as a representative area with a humid climate in this study. Initially, using the Multi-Criteria Evaluation Method, a fire risk map was created by analyzing natural and human factors, and vulnerable areas were identified. Then, the relationship between key elements such as meteorological conditions, Land Surface Temperature (LST), and precipitation, with the occurrence of fire in different years was investigated. CHIRPS and Landsat data were utilized to assess LST changes and precipitation. 23-year changes in fire occurrence areas in GNP were acquired using MODIS products. The results of the data analysis showed that the highest number of fires occurred in forest areas, and in the fire risk prediction map, the extremely high-risk class is completely consistent with the ground truth data. The assigned weights, derived from expert opinions, highlight the substantial significance of elevation, and distance from roads and settlements. Additionally, the effectiveness of the model in providing reliable forecasts for fire risks in GNP is highlighted by the ROC curve with an AUC value of 0.83. Forest fires within GNP exhibit a distinct seasonality, predominantly occurring from July to December. During the warmer months, by coinciding with summer excursions, human activities may contribute to the ignition of fires. In 2013 and 2014, rising fire incidents correlated with elevated temperatures, hinting at a potential connection. GNP fires showed an upward trend with higher monthly LST and a downward trend with increased annual precipitation. The results showed that there is a relationship between LST, precipitation, and the occurrence of fire in GNP. Approximately 176.15 ha of GNP's forest areas have been destroyed by fires over the last two decades. This research demonstrated that there is a dynamic interaction between environmental conditions and fire incidents. By considering these factors, managers and environmental planners can develop effective strategies for managing and preventing forest fire risks.

Problems of rehabilitation and recovery of military servicemen under special conditions

The problem of this study is the lack of a detailed study of physical rehabilitation (help) and recovery, which is necessary for all military personnel who took and participate in combat operations. The purpose of the study is to analyze and reveal the physical rehabilitation of servicemen in Ukraine during martial law. Research methods were used in the article such as: deduction method (from general to basic in the field of physical rehabilitation research in Ukraine), analysis method (to establish existing and effective physical rehabilitation for servicemen during martial law in Ukraine), generalization method (for writing conclusions and proposals), etc. The main results of the study: the types of physical rehabilitation that military personnel undergo to restore physical health are considered.(Physical rehabilitation for military personnel during martial law includes: therapeutic physical culture, natural physical factors, hardening, therapeutic massage, manual therapy, physical therapy, mechanotherapy, occupational therapy, kinesitherapy, occupational therapy, reflexology. Conducting rehabilitation activities for military personnel has its own characteristics due to participation in combat actions that were accompanied by excessive physical and psychological stress, generating powerful combat stress, demobilized fighters, returning home, note that their psyche is not adapted to peaceful civilian lifeThe scientific novelty of the research results is due to a detailed study of the problem of rehabilitation and recovery of servicemen during martial law in Ukraine. Conclusions and suggestions: the lack of rehabilitation doctors, the lack of clear packages of services for the rehabilitation and recovery of servicemen during martial law, the lack of quick communication between military units, medical institutions and the military medical commission regarding the rehabilitation and recovery of servicemen - these are all the gaps of today. To solve existing problems, it is necessary to: stimulate doctors to study in the field of rehabilitation; legislatively regulate the possibility of releasing disabled persons who have acquired a disability or those who were already disabled and went to the front as volunteers; to create a physical and psychological rehabilitation program for each serviceman who needs rehabilitation and recovery; creation of the concept of rehabilitation of soldiers released from captivity, etc.

Study of the specifics of the physical training of National Guard servicemen in extreme conditions

Depending on the professional duties of the National Guardsmen of different units, specific requirements for their professional readiness are established, including the necessary level of physical fitness for the effective performance of official tasks. Extraordinary circumstances caused by social, natural or man-made factors complicate activities and place high demands on the psychological stability and special physical fitness of employees. To improve the process of physical training of national guardsmen, it is important to take into account the peculiarities of their professional activity in extreme conditions. This involves the analysis of requirements for psychological, psychophysiological and physical readiness to perform official duties. The specifics of the activities of Ukrainian National Guard servicemen are associated with extreme factors, such as danger, extraordinary dynamics of events, lack of time and information, uncertainty of the situation, analysis of unstructured information, urgency of solving tasks and high responsibility for decisions. One of the components of the professional readiness of the soldiers of the National Guard of Ukraine is physical fitness, which includes readiness for high-intensity physical exertion, control over weapons and equipment, readiness for specialized movements when shooting, and endurance in resisting negative factors of service-combat activity. The conducted study outlined directions for improving the process of physical training at the National Guard of Ukraine unit. The requirements for the professional readiness of fighters of various sections of the the National Guard of Ukraine have been determined. This made it possible to develop an algorithm for the formation of the physical training process depending on the specifics of the service of specialists of various profiles.

Research on The Spatial Heterogeneity of National Physical and Mental Health in China Based on Numerical Simulation

Studying the spatial interactions between socio-economic and natural (SEN) factors and physical health (PF) can help improve national physical and mental health and develop health policies. In order to deeply analyze the relationship between social and economic environment, sports activities, and national physical and mental health, and improve the level of national physical and mental health, this study used mathematical numerical analysis methods using MATLAB and ArcGIS software to determine the determining factors of PF differences in China. The reported National Fitness Composite Index (NFCI) in China was extracted from the National Physical and Mental Health Fitness Monitoring Bulletin in 2015. The SEN factors were gathered from the China Statistical Yearbook in 2015. The OLS model and GWR model were then utilized to investigate the SEN factors of the NFCI. We found that the NFCI of each province had a strong relationship with the natural environment. The NFCI of the eastern coastal regions was higher but also similar to that of the central and western regions. It was also found that the impact of the natural environment on national physical and mental health fitness was greater than that of social and economic factors. Temperature and hours of sunshine were major environmental factors. Annual hours of sunshine (ANNsun, hours), health care expenditure (HEAexpe, Chinese yuan), annual temperature (ANNtem, °C), road distance (ROAdis, kilometers) and annual rainfall (ANNrai, millimeters)are socioeconomic and natural (SEN) determinants of factors and physical fitness (PF). We should increase physical exercise, change our concepts of health, develop a healthy lifestyle and improve our physical fitness in accordance with the national fitness strategy. The regression coefficients obtained by the GWR model show significant differences, indicating that the degree of influence of social, economic, and natural factors on national physical fitness varies significantly with geographical regions..

Study on the geographic distribution and influencing factors of Dai settlements in Yunnan based on geodetector

The Dai people are primarily found in Yunnan Province, China, and have a long heritage there. The latest national census reports that Yunnan is home to 1,259,000 individuals of the Dai ethnic group. This study focuses on 3504 Dai settlements in Yunnan, identified through county records. Using the ArcGIS spatial analysis platform, we first evaluated their settlements’ spatial distribution patterns using metrics like the nearest neighbor index and geographic concentration index. Then, we applied geodetector to investigate the underlying mechanisms of their distribution. The results reveal that: (1) Dai settlements in Yunnan Province generally have a cohesive spatial distribution; at the provincial level, however, there is an uneven distribution pattern, with many densely populated areas and a pattern of “two cores, one belt, one area, and two points”; (2) The Dai settlements predominantly occupy the third gradient of the vertical zonation, with Dai gathering settlements primarily found in the Lancang, Ayeyarwaddy, and Red River basins. Conversely, Dai mixed settlements are mainly situated in the Lancang, Red, and Nu River basins; (3) Analysis via geodetector indicates that ethnocultural factors are the most significant in determining the spatial distribution of the Dai settlements, followed by socio-economic and natural factors; (4) The distribution of settlements is significantly influenced by the proportion of the Dai population within these settlements. Dai gathering settlements are typically located on flat slopes with elevations ranging from 500 to 1000 m and slopes of 0°–5°. Meanwhile, Dai mixed settlements are found on gentle slopes with elevations of 1000–2000 m and slopes of 5°–15°. The study reveals that the location of Dai settlements is strongly influenced by environmental considerations and has a significant explanation from similar origins.

GEMAS: Phosphorus in European agricultural soil - sources versus sinks at the continental-scale - the geological perspective

Phosphorus (P) is one of the essential elements for life on Earth. As a major nutrient it is needed for healthy growth both in plants and living organisms. Although the abundance of P in the Earth's upper continental crust is relatively high (655 mg/kg), many soil types are poor in available phosphorus. The main natural factors controlling the availability of P in soil are pH, mineralogy, and formation of insoluble complexes with Al and Fe under acidic, and with Ca and Mg under alkaline soil conditions. Superimposed weathering processes and climate contribute strongly to P mobility and availability. Additionally, a large fraction of total soil P is in organic forms, which are not directly available to plants. Phosphorus is a major component in fertilisers and thus a significant source of anthropogenic P in soil and water.In the agricultural soil samples that were collected during the Geochemical Mapping of Agricultural and grazing land Soil (GEMAS) project, the total P concentrations (XRF, median 786 m/kg) are only slightly higher than those extracted by hot aqua regia (AR, median 653 mg/kg), while the median concentration in the weak MMI® cold extraction is as low as 4.1 mg/kg. The AR results show very low P concentrations over the coarse-grained sandy sediments of the last glaciation in central and northern Europe and in calcareous soil. The southern limit of the last glaciation is visible as a concentration break on the geochemical maps. In general, north-eastern and north-western Europe are marked by high P values, probably related to cold and humid climate and enrichment in humus-rich coastal soil. The spatial distribution of P at the continental-scale is dominated by geogenic and climatic factors, and the anthropogenic influence is difficult to assess and quantify.

Trend detection and depletion effects evidence in time series of groundwater levels in the southern sector of the left bank of the Tagus-Sado Basin (Portugal, Iberian Peninsula)

In the last 20 years in Portugal, water resources have been affected to the point that water storage has decreased by 20% since 2000. Creating strategies to manage water resources requires a comprehensive understanding of the factors influencing water storage and their effects over time. This study is focused on the evolution of Groundwater Deep Levels (GDL) by applying a two-phase trend analysis methodology to examine the dynamic changes in GDL within a series of monitoring wells located in the Central and Southern sectors of the Left Bank of the Tagus-Sado Cenozoic age Basin, situated in Portugal In the initial phase of trend analysis, Factorial Analysis of Mixed Data (FAMD) was employed and posteriorly the Hierarchical Classification Analysis (HCA). These techniques enabled us to identify distinct GDL trend profiles and generate interpretative maps illustrating their spatial distribution. In the second phase, the non-parametric Mann–Kendall Analysis (MKA) and Innovative Trend Analysis (ITA) were applied, allowing for a quantified confirmation of the different trend profiles previously detected. These techniques allowed the identification of positive and negative hydrodynamic trends in distinct sections of the Basin. In the SE sector they are characterized by a significative increase of GDL associated with overexploitation and in the Central sector with a decrease of GDL. Nevertheless, significant depletion effects can result from natural factors such as prolonged droughts, and in certain regions, changes in geological and hydrothermal dynamics, such as Alpine-age faults, graben, and horst structures, may account for these alterations.

Utilization of Satellite Imagery for Mapping the Distribution of Seagrass on Buhung Pitue Island

Buhung Pitue Island has seagrass beds those which are spread almost evenly along its coast. Research using remote sensing technology in an effort to support seagrass conservation in Indonesia needs to be carried out. Spatial data is relatively easy to obtain because there are many types of images with various spatial resolutions. The image can be obtained on google earth. Analysis of the distribution of seagrass areas was obtained by digitizing on screen in ArcGIS software, namely in seagrass areas where the boundaries are known. Digitizing is conducted by enlarging the seagrass area in the downloaded image, performing radiometric and geometric corrections, and digitizing to create a shapefile (shp) storing the location, shape, and attributes of geographic features. The seagrass distribution area of Buhung Pitue Island was of 36.5 Ha in 2014 and was of 39.6 in 2021. The rate of change in area from 2014 to 2021 was of 0.085% (an increase of 3.1 ha). The distribution area of seagrass has increased due to natural factors and restrictions on human activities during the COVID-19 pandemic. In addition, another factor supporting the increase in seagrass distribution is the abundance of Enhalus acoroides seagrass species growing and spreading over long distances. The sea surface temperature was high, which was 30.37 °C, while the current speed was categorized as slow because it was around 0.01 m/s. Although the results are obtained from high-resolution imagery, an accuracy test still needs to be conducted.

Household energy consumption of herders on the Qinghai–Tibetan Plateau: Profiles of natural and socio-economic factors

In remote areas, people experiencing persistent poverty still face challenges related to energy shortages and air pollution. Due to the escalating global climate change crisis, herding communities in the Qinghai–Tibetan Plateau remain vulnerable to significant threats related to energy security and accessibility. These communities are vulnerable because they occupy underdeveloped regions and depend heavily on traditional energy sources. To explore this issue, we conducted a comprehensive questionnaire-based survey involving 473 herders across 13 counties on the Qinghai–Tibetan Plateau. The findings revealed that per capita energy consumption in herder households averaged 2021.793 kgce/year. Noncommercial energy sources constituted a substantial 61.66%, with the predominant one being cow dung, and refrigerators are the highest energy consumption household appliances. By applying geographically weighted regression (GWR), we examined seven key natural and socio-economic factors influencing solid energy use. These factors included annual per capita household income, the highest level of education, indoor and outdoor oxygen concentrations, the labor force population, housing size, and altitude. Notably, the first three variables exhibited negative correlations, while the rest demonstrated positive correlations. The impact of oxygen concentrations on household energy consumption was particularly significant, as demonstrated by the notable correlation. In this study, we elucidated the intricate structure and determinants of energy consumption structure within herders.

Occurrence, source modeling, influencing factors and exposure assessment of polycyclic aromatic hydrocarbons in water sources: A mega-study from mainland China

This study investigates the composition and distribution of 16 priority polycyclic aromatic hydrocarbons (PAHs) in 70 water samples collected from centralized drinking water sources (CDWSs) across 30 provinces (cities) in mainland China. Additionally, water quality and socio-economic data were collected to determine the influencing factors. The study discovered that the total concentrations of 16 priority PAHs (Σ16PAHs) varied from 0.17 to 176.71 ng/L (mean: 56.49 ± 38.58 ng/L). Lakes and reservoirs had significantly higher concentrations of PAHs than groundwater. The primary pollutants were low-molecular-weight (LMW) PAHs, such as phenanthrene, naphthalene, and fluorene. There was a strong correlation between LMW PAHs and Σ16PAHs (p < 0.05). The mean Σ16PAHs in the seven geo-environmental zones were ranked as follows, under the comprehensive influence of emission density, natural, and social environmental factors: Northwest China (78.42 ± 66.96 ng/L) > Northeast China (73.70 ± 33.23 ng/L) > East China (64.35 ± 45.66 ng/L) > North China (50.95 ± 31.87 ng/L) > Southwest China (44.05 ± 32.56 ng/L) > Central China (41.68 ± 19.44 ng/L) > Southern China (40.99 ± 16.54 ng/L). The source modeling analysis revealed that the majority of PAHs came from chemical production and metal smelting (42.36%), as well as from the combustion of coal, wood, and biomass (34.17%), and other mixed sources. In addition, the study found a strong correlation between water quality and socio-economic factors with concentrations of PAHs, indicating that these factors may contribute to the re-enrichment, transport, and transformation of PAHs in overlying water to varying degrees. The mean incremental lifetime cancer risk (ILCR) was lower than the risk threshold. These findings provide scientific references for managing hazardous substances in the aquatic environment.

What are the dominant drivers and optimal thresholds for a healthy ecosystem in the Yellow River Basin, China? from a perspective of nonlinear nexus

Identifying the dominant factors influencing ecosystem health and their optimal thresholds is essential for the management and restoration of ecosystems. Most of the works, however, have less detected the importance level of individual factors, especially their changes over time and scale, and rarely determined their threshold effects on ecosystem health (EH), which seriously hinders the formulation of targeted policies for sustainable ecosystem management. To address these research gaps, we present an innovative visualization approach to reveal importance changes in natural and anthropogenic variables and their nonlinear coupling process with EH in the China’s Yellow River Basin (YRB) in the last two decades. Results show that (i) Although the EH in the YRB has improved slightly in the past 20 years, it is still not optimistic and shows distinct spatial heterogeneity. (ii) The impact of human activities on the ecosystem health of the YRB has increased and increasingly plays a decisive role, while that of the natural aspect has decreased recently. Specifically, environmental factors (slope, NDVI, and annual temperature) are the dominant factors affecting the upstream EH. Midstream EH is significantly affected by the synergistic effect of natural and anthropogenic factors, but the importance of the proportion of built-up land is intensified (ranked from 8th to 4th). Anthropogenic factors exert the greatest influence on downstream EH variation, especially for population density whose importance order rising from 7th to 2nd. (iii) By illustrating the nonlinear response curves of EH at multi-scale, the tipping point caused ecosystem deterioration in the YRB is explored and the optimal thresholds of leading factors oriented towards the most effective ecosystem conservation goal are obtained. These results help precisely identify the current health status of YRB's ecosystem, as well as providing a valuable reference for moderate restoration standards and sustainable ecosystem management.