Search Results (27)

Background: Disruptions in the mesh of the ecosystem come with implications that severely harm the sustainability and the equilibrium of life. Interactions of humans, animals, and many other organisms, along with the whole ecological complex, have given birth to zoonotic diseases, which can vary in type and burden. Collaborative efforts put into the prioritization of environmental, animal, and human health are envisioned as “One Health”. Understanding vector ecology and the varying mechanistic ways of transmission is crucial for constructing effective One Health surveillance tools and warning systems. Methods: We identified the literature available concerning the subject matter. We utilized scholarly databases to gather research for the last 10 years using predefined keywords. Objectives: This review aims to synthesize current knowledge on the interconnection between climate discrepancies, ecological alarms, and the emergence and spread of zoonotic diseases. We attempted to provide recommendations for future research and policy interventions. Results: Human activities have significantly impacted disease-carrying vectors and wildlife habitats, aiding their proliferation and the spillover of diseases. Global frameworks incorporating One Health principles enhance global preparedness for future health threats. Applying the integrated One Health Surveillance has strengthened early warning systems. Interdisciplinary collaborations and tools like OH-EpiCap, a comprehensive tool that assesses and enhances the capacities of One Health surveillance systems, have significantly contributed to responding to infectious disease outbreaks, as seen in the Netherlands, reducing the risk of tick-borne diseases. Conclusions: Strides have been made with comprehensive processes that identify and prioritize zoonotic diseases of most significant concern and burden, such as OHZDP, approaches like One Health, and other theories considered. A proactive and integrated approach will build resilience against potential outbreaks and ensure a healthier future for our planet and its inhabitants. Full article

This research aims to develop mitigation and adaptation strategies for greenhouse gas emissions Thailand in accordance with Climate-Smart Agriculture policies. The research employs a mixed-methods approach, integrating both quantitative and qualitative research as a crucial framework for impact analysis and an early warning tool for the government in achieving sustainability. On the quantitative side, an advanced model called the Longitudinal Mediated Moderation Analysis Based on the Fuzzy Autoregressive Hierarchical Process (LMMA-FAHP) model has been developed. This model meets all validity criteria, shows no signs of spuriousness, and outperforms previous models in terms of performance. It is highly suitable for policy formulation and strategic planning to guide the country’s long-term governance toward achieving net-zero emissions by 2065. The findings indicate that the new scenario policy, with an appropriateness rating of over 80%, includes factors such as the clean technology rate, biogas energy, biofertilizers, organic fertilizers, anaerobic digestion rate, biomass energy, biofertilizer rate, renewable energy rate, green material rate, waste biomass, and organic waste treatments. All indicators demonstrate a high sensitivity level. When the new scenario policy is incorporated into future greenhouse gas emissions forecasts (2025–2065), the research reveals a declining growth rate of emissions, reaching 78.51 Mt CO₂ Eq., with a growth rate of 11.35%, which remains below the carrying capacity threshold (not exceeding 101.25 Mt CO₂ Eq.). Moreover, should the government adopt and integrate these indicators into national governance frameworks, it is projected that greenhouse gas emissions by 2065 could be reduced by as much as 36.65%, significantly exceeding the government’s current reduction target of 20%. This would enable the government to adjust its carbon sequestration strategies more efficiently. Additionally, qualitative research was conducted by engaging stakeholders from the public sector, private sector, and agricultural communities to develop adaptive strategies for future greenhouse gas emissions. If the country follows the research-driven approach outlined in this research, it will lead to effective long-term policy and governance planning, ensuring sustainability for Thailand. Full article

The marine ecological carrying capacity (MECC) of marine ranching serves as a crucial indicator for assessing the conservation effect of fishery resources and forms a significant basis for scientific management of coastal fisheries. The environmental impacts on the MECC of marine ranching in the northern South China Sea were analyzed quantitatively by employing Generalized Additive Models (GAMs), which have been successfully applied to the study of the relationship between fishery resources and environmental factors, and factor analysis, using satellite and survey observations. Results showed that 95.40% of the total variation in MECC was explained by these factors. Based on the GAMs, the most important factor was Year (calendar years), with a contribution of 66.20%, followed by Chlorophyll a concentration (Chl-a), Sea Surface Temperature (SST), Dissolved Inorganic Nitrogen (DIN) and Water Current, with contributions of 20.60%, 4.40%, 3.60%, and 0.60%, respectively. The findings of this study inspire us to establish a long-term marine ranching resource and environment monitoring platform, and an early warning and forecasting expert decision-making system, providing scientific references for planning and management of coastal marine ranching. Full article

The Yangtze River Economic Belt (YREB), spanning 11 provinces and municipalities across China, is of paramount importance due to its high economic development and strategic role in national distribution. However, the YREB, which has experienced rapid economic growth, faces challenges resulting from its previously expansive development model, including regional resource and environmental issues. Consequently, a systematic analysis encompassing socio-economic, ecological, and resource-environmental aspects is vital for a comprehensive and quantitative understanding of the YREB’s overall condition. This study explores resource and environmental carrying capacity (RECC) by constructing an integrated framework that includes remote sensing data, geographic information data and social statistical data, which allows for a precise analysis of RECC dynamics from 2010 to 2020. The findings demonstrate an upward trend in the overall quality of RECC from 2010 to 2020, achieving higher grades over time. However, there is significant spatial heterogeneity, with a notable decrease in RECC levels moving from the eastern to the western regions within the YREB. Moreover, low-level RECC areas situated in the northwest of the YREB, show a trend of moving toward regions of higher altitude from 2010 to 2020 based on analysis using the standard deviation ellipse (SDE) method. When considering to the three major urban agglomerations within the YREB, overall RECC in middle and lower agglomerations is generally stable and on an upward trend while cities in upper reaches exhibit significant variation and fluctuations, highlighting them as areas requiring future focus. Therefore, specific indicators were applied to monitor RECC risk for each of these three agglomerations, respectively, after which optimized strategies could be proposed based on different early warning levels. Ultimately this study allows local authorities to implement timely and effective interventions to mitigate risks and promote sustainable development. Full article

To improve the water resources carrying capacity of the Xiangjiang River Basin and achieve sustainable development, this article evaluates and predicts the Xiangjiang River Basin’s water resources carrying capacity level based on county-level units. This article takes 44 county-level units in the Xiangjiang River Basin as the evaluation target, selects TOPSIS and the entropy weight method to determine weights, calculates the water resources carrying capacity level of the evaluation sample, uses a BP neural network model to calculate the predicted water resources carrying capacity level for the next 5 years, and adds the GIS method for spatiotemporal analysis.(1) The water resources carrying capacity of the Xiangjiang River Basin has remained relatively stable for a long period, with overloaded areas being the majority. (2) There are relatively significant spatial differences in the carrying capacity of water resources: Zixing City, located upstream of the tributary, is far ahead due to its possession of the Dongjiang Reservoir; the water resources carrying capacity in the middle and lower reaches (northern region) is generally higher than that in the upper reaches (southern region). (3) According to the BP neural network model prediction, the water resources carrying capacity of the Xiangjiang River Basin will maintain a stable development trend in 2022, while areas such as Changsha and Zixing City will be in a critical state, and other counties and cities will be in an overloaded state.This study has important references value for the evaluation and early warning work of the Xiangjiang River Basin and related research, providing a scientific and systematic evaluation method and providing strong support for water resource management and planning in Hunan Province and other regions. Full article

In order to safeguard the health of river ecosystems and maintain ecological balance, it is essential to rationally allocate water resources. This study utilized continuous runoff data from 1967 to 2020 at the Zhouqu Hydrological Station on the Bailong River. Five hydrological methods, tailored to the hydrological characteristics of the Zhouqu hydrological cross-section, were employed. These methods included the improved dynamic calculation method, the NGPRP method, the improved monthly frequency computation method, the improved RVA method, and the Tennant method. Ecological flow calculations were conducted to determine the ecological flow, with analysis carried out through the degree of satisfaction, economic benefits, and the nonlinear fitting of the GCAS model. We established an ecological flow threshold and early warning program for this specific hydrological cross-section. Ecological flow values calculated using different methods for each month of the year were compared. The improved RVA method and Tennant method resulted in small values ranging from 4.05 to 36.40 m³/s and 7.65 to 22.94 m³/s, respectively, with high satisfaction levels and economic benefits, but not conducive to ecologically sound development. In contrast, the dynamic calculation method, NGPRP method, and improved monthly frequency calculation method yielded larger ecological flow values in the ranges of 21.79–97.02 m³/s, 23.90–137.00 m³/s, and 28.50–126.00 m³/s, respectively, with poor fulfillment and economic benefits. Ecological flow thresholds were determined using the GCAS model, with values ranging from 16.72 to 114.58 m³/s during the abundant water period and from 5.03 to 63.63 m³/s during the dry water period. A three-level ecological warning system was proposed based on these thresholds, with the orange warning level indicating optimal sustainable development capacity for the Zhouqu Hydrological Station. This study provides valuable insights into the scientific management of water resources in the Bailong River Basin to ensure ecological security and promote sustainable development. Full article

Basalt Fiber Reactive Powder Concrete (BFRPC) semi-prefabricated composite capping beam structures can effectively improve the shortcomings of ordinary concrete capping beams' construction difficulties and insufficient bearing capacity. In this study, with the objective of analyzing the shear damage and damage characteristics of a prefabricated BFRPC capping beam formwork, structural damage tests under different levels of loading were carried out to obtain the mechanical parameters of key nodes. Acoustic emission (AE) and Digital Image Correlation (DIC) techniques were used to acoustically and visually characterize the formwork damage. The research results showed that the damage stage of the capping beam formwork was divided, and an early damage warning method was proposed based on the acoustic parameters. Using the DIC technique to identify the crack width evolution pattern during the shear process, it was found that the cracks expanded steadily as the load increased. Combining the experimental and simulation results as well as the Subdivision Superposition Theory, a half-open stirrup strength discount factor $\beta$ was introduced and suggested to take a value of 0.79. The formula for calculating the shear capacity of BFRPC capping beam formwork is proposed to provide a theoretical basis for its application in prefabricated assembled structures. Full article

Water scarcity has significantly hampered China’s economic, social, and environmental development. Ensuring sustainable water utilization is crucial given the mounting water stress accompanying continuous economic growth. A quantitative water resource forewarning model was constructed using the vector autoregressive (VAR) model. By analyzing the key indicators related to water systems and GDP data from 2001 to 2022, the VAR model revealed the long-term dynamic correlation between water consumption and economic growth using generalized impulse response, co-integration, and predictive variance decomposition analyses. The results revealed the presence of a long-term equilibrium between water consumption and economic growth, with a stable co-integration relationship and an optimal lag period of one year. The positive impact of water consumption on economic development increased during the 2001–2022 period, indicating a rising dependence of GDP on water resources. Water usage rose with economic development, while the water resource carrying capacity remained high and continued to grow. Based on the generalized impulse response, co-integration, and predictive variance decomposition analyses, this study predicted water-use-related indicators, providing vital early warnings for China’s water environment carrying capacity from 2023 to 2050. This enabled informed decision-making and fostered sustainable water management practices for the future. Full article

The Yellow River Basin is an essential ecological barrier in China, but it is relatively underdeveloped. The human–land relationship needs to be coordinated, and the ecological environment is fragile, which seriously restricts the sustainable development of the urban agglomeration in the Yellow River Basin. In this study, a “five-dimensional integrated” comprehensive carrying capacity evaluation model is constructed using the five dimensions of water, land, ecology, monitoring, and early warning to evaluate its resource carrying capacity quantitatively. It constructs an early warning system of the resource carrying capacity based on the quantitative evaluation results and monitors the state of the resource carrying capacity. The results show that (1) seven major urban agglomerations’ populations, grain productions, and land are surplus, and 50.85% of prefecture-level cities have food surpluses regarding human–food relationships. (2) There are shortages in the urban agglomeration’s water resources and a deficit in the water resource carrying capacity. (3) The average ecological carrying capacity index is 0.519, indicating a state of ecological affluence. (4) The comprehensive resource carrying capacity is defined as level-three heavy-load conditions, while 67%, 22%, and 14% of cities have level-one, -two, and -three heavy-load conditions, respectively. This study can aid in the monitoring of the resource carrying status of the Yellow River Basin. These results provide a scientific basis for effectively restraining the utilization and development of natural resources in the Yellow River Basin. It can also provide a research paradigm for the world’s river basins, as well as the sustainable development of man and nature in the world. Full article

African swine fever has damaged the foundation of China’s hog industry, caused a serious decline in hog production, highlighted the contradiction between supply and demand in the pork market, and led to major economic and social impacts. The industrial resilience of 31 Chinese provinces to African swine fever shock and its spatial and temporal differentiation characteristics from 2018 to 2021 were measured in this study from the two dimensions of resistance and recoverability. Using Geodetector, the key factors influencing the resilience of China’s hog industry were explored. The results showed that 2018–2019 and 2020–2021 represented the resistance and recovery periods of the hog industry under African swine fever shock, respectively, with poor resilience characterizing the resistance period and improved resilience characterizing the recovery period. At the early stages of the African swine fever outbreak, the hog industries in Tianjin, Shanxi, Guangxi, and Yunnan had robust resistance due to the slaughter rate, economic level, mortality rate, carcass weight, and culling rate in those areas. At the most severe stage of the outbreak, resistance was generally poor in all provinces due to the slaughter rate, per capita consumption, and scale level at the time. During the period of rapid recovery in hog production, the recoverability of each province was very strong due to the industrial structure, culling rate, economic level, and resource carrying capacity at that time. During the reasonable adjustment period of hog production capacity, the recoverability based on the breeding sow inventory in 13 provinces, including Henan, Shandong, and other large hog-breeding provinces, was negative due to the scale level, slaughter rate, per capita consumption, and resource carrying at that time. Taking measures to enhance the resilience of the hog industry, strengthen the prevention and control of hog epidemics, improve the monitoring and early warning mechanisms, and enhance the ability of the hog industry to cope with major animal epidemics is recommended. Full article

In order to accurately analyze the load supply capability of power systems with high penetration of renewable energy generation, this paper proposes a probabilistic available load supply capability (ALSC) forecasting method. Firstly, the optimal input features are selected by calculating the maximal information coefficient (MIC) between the input features and the target output. Based on this, a stacking ensemble learning model is applied for the prediction of wind power, photovoltaic power and load power. Secondly, the distributions of the forecasting objects are obtained based on forecasting errors and the error statistics method. Finally, the forecasting distributions of wind power, photovoltaic power and load are set as the parameters of a power system, and then probabilistic ALSC is calculated using Latin hypercube sampling (LHS) and repeated power flow (RPF). In order to simulate a more realistic power system, multiple slack buses are introduced to conduct two types of power imbalance allocations with novel allocation principles during the RPF calculation, which makes the ALSC evaluation results more reasonable and accurate. The results of probabilistic ALSC forecasting can provide a reference for the load power supply capacity of a power system in the future, and they can also provide an early warning for the risk of ALSC threshold overlimit. Case studies carried out on the modified IEEE 39-bus system verify the feasibility and effectiveness of the proposed methods. Full article

Underground coal mining can cause the deformation, failure, and collapse of the overlying rock mass of a coal seam. If the mining design, monitoring, early warning, or emergency disposal are improper, in that case, it can often lead to mining disasters such as roof falls, water inrush, surface collapse, and ground fissures, seriously threatening the safety of mine engineering and the geological environment protection in mining areas. To ensure the intrinsic security of the entire coal mining process, aspace–time continuous sensing system of overburden deformation and failure was developed, which breaks through the limitations of traditional monitoring methods that characterize the evolution process of overlying rock deformation and ground subsidence. This paper summarizes the classification of typical overburden deformation and failure modes. It researches the space–time continuous sensing of rock–soil mass above the coal seam based on Distributed Fiber Optic Sensing (DFOS). A multi-range strain optical fiber sensing neural series from micron to meter was developed to achieve synchronous sensing of overburden separation, internal micro–cracks, and large rock mass deformation. The sensing cable–rock mass coupling test verified the reliability of the optical fiber monitoring data. The sensing neural network of overburden deformation was constructed using integrated optical fiber layout technology on the ground and underground. Different sensing nerves’ performance and application effects in overburden deformation and failure monitoring were compared and analyzed with field monitoring examples. A physical model was used to carry out the experimental study on the overburden subsidence prediction during coal mining. The results showed that the optical fiber monitoring data were reliable and could be used to predict overburden subsidence. The reliability of the calculation model for overlying rock subsidence based on space–time continuous optical fiber sensing data was verified in the application of mining subsidence evaluation. A systematic review of the shortcomings of current overburden deformation observation technology during coal mining was conducted, and a space–time continuous sensing system for overburden deformation and failure was proposed. This system integrated sensing, transmission, processing, early warning, decision-making, and emergency response. Based on the fusion of multi-parameter sensing, multi-method transmission, multi-algorithm processing, and multi-threshold early warning, the system realized the real-time acquisition of space–time continuous information for the overburden above coal seams. This system utilizes long-term historical monitoring data from the research area for data mining and modeling, realizing the prediction and evaluation of the evolution process of overburden deformation as well as the potential for mining subsidence. This work provides a theoretical reference for the prevention and control of mining disasters and the environmental carrying capacity evaluation of coal development. Full article

Ecologically fragile areas in China account for more than half of its land area. Performing early warning assessments and trend analyses of resource and environment carrying capacity in ecologically fragile areas can lay a scientific foundation for ecological conservation in the areas. Based on the connotation of resource and environment carrying capacity, an early warning index system of resource and environment carrying capacity in Altay prefecture was constructed from the three aspects natural resource carrying capacity, eco-environment carrying capacity, and economic and social support capacity. The grey relational projection method model was used to analyze the current alarm situation of the resource and environment carrying capacity in Altay prefecture from 2011 to 2020, and then the back propagation (BP) neural network and a mathematical statistics software were used to predict the evolution of the alarm situation of the resource and environment carrying capacity in Altay prefecture from 2021 to 2025. The results demonstrated that (1) the natural resource carrying capacity subsystem was the main system of the development of the resource and environment carrying capacity in Altay prefecture, and its impact on the resource and environment carrying capacity in Altay prefecture was greater than the eco-environment carrying capacity and economic and social support capacity; (2) the resource and environmental carrying capacity of Altay prefecture showed a slight upward trend from 2011 to 2020, although the range was constrained and the level of warning remained “moderate warning”. A spatial pattern of “weak in the middle, strong in the two poles” was exhibited by the warning scenario about the carrying capacity of each county and city. Except for the warning of Habahe County and Qinghe County, where the warning was slightly worse than that in 2020, the warning of resource and environment carrying capacity in Altay prefecture and other counties and cities would show a trend of fluctuation and decline from 2021 to 2025. However, the degree of alarm did not change substantially and remained at the level of “moderate warning”; (3) the main factors restricting the mitigation of the warning of resource and environment carrying capacity in Altay prefecture included a low soil fertility index, a small total reservoir capacity, low per capita mineral resource reserves, a low water resource development and utilization rate, a low comprehensive utilization rate of industrial solid waste, and a low land output rate. Full article

The ecological security of cultivated land critically depends on maintaining the quality of the land under cultivation. For the security of the nation’s grain supply, the evaluation and early warning of cultivated land quality (CLQ) are essential. However, previous studies on the assessment of the ecological safety of CLQ only rigidly standardized the assessment indicators and failed to investigate the positive and negative trends and spatiotemporal driving factors of the indicators. The main objective of this study was to develop a drive–pressure–state–response (DPSR) model to identify the hierarchical structure of indicators, using an improved matter–element model to assess the CLQ in the black soil region of northeastern China from 2001 to 2020. A panel data model was employed to explore the crucial drivers of CLQ warnings. The findings reveal that socioeconomic development has a potential impact on the improvement of CLQ. CLQ is generally in a secure state, with 69.71% of cities with no warnings and only 3.46% and 0.13% of cities under serious and extreme warnings, respectively. Compared with 2001, the CLQ in 2020 effectively improved by socioeconomic development and the conservation and reasonable utilization of arable land. According to the early warning results, the cultivated land in the northern regions was of higher quality than that in the southern regions. Moreover, the CLQ was significantly positively correlated with the agricultural GDP growth rate, grain yield per unit of cultivated land area, annual precipitation, and the habitat quality index, and was significantly negatively correlated with land carrying capacity. The findings of this study can provide a scientific and targeted basis for black soil conservation and utilization. Full article

Aquifer surveillance is key to understanding the dynamics of groundwater reservoirs. Attention should be focused on developing strategies to monitor and mitigate the adverse consequences of overexploitation. In this context, ground surface deformation monitoring allows us to estimate the spatial and temporal distribution of groundwater levels, determine the recharge times of the aquifers, and calibrate the hydrological models. This study proposes a methodology for implementing advanced multitemporal differential interferometry (InSAR) techniques for water withdrawal surveillance and early warning assessment. For this, large open-access images were used, a total of 145 SAR images from the Sentinel 1 C-band satellite provided by the Copernicus mission of the European Space Agency. InSAR processing was carried out with an algorithm based on parallel computing technology implemented in cloud infrastructure, optimizing complex workflows and processing times. The surveillance period records 6-years of satellite observation from September 2016 to December 2021 over the city of Chillan (Chile), an area exposed to urban development and intensive agriculture, where ~80 wells are located. The groundwater flow path spans from the Andes Mountain range to the Pacific Ocean, crossing the Itata river basin in the Chilean central valley. InSAR validation measurements were carried out by comparing the results with the values of continuous GNSS stations available in the area of interest. The performance analysis is based on spatial analysis, time series, meteorological stations data, and static level measurements, as well as hydrogeological structure. The results indicate seasonal variations in winter and summer, which corresponds to the recovery and drawdown periods with velocities > −10 mm/year, and an aquifer deterioration trend of up to 60 mm registered in the satellite SAR observation period. Our results show an efficient tool to monitor aquifer conditions, including irreversible consolidation and storage capacity loss, allowing timely decision making to avoid harmful exploitation. Full article