Pub Date : 2024-08-02DOI: 10.3389/feart.2024.1445990
Tong Li, Ming Chen, Bo-wen Guo, Li Song, Bing Fan, Shan-shan Cui
The fragmentation size distribution is an important index to evaluate blasting effect. Based on stress wave theory, a blasting fragmentation distribution model is established, and the key influencing factors were clarified. Then, the distribution characteristics of rock fragmentation in water-coupled blasting and air-coupled blasting were compared and verified by numerical simulation and field test. The results show that the rock blasting fragmentation size is negatively correlated with borehole pressure and unit explosive consumption when blasting rock is determined. The existence of water slows down the attenuation of blasting load, prolongs the duration, and makes the blasting pressure transmitted to hole wall significantly greater than air-coupled one, which is equivalent to increasing the unit explosive consumption. Moreover, the rock fracture development speed and fragmentation degree of water-coupled blasting is significantly higher than air-coupled blasting. Comprehensively determined in same charging parameters, water-coupled blasting compared with air-coupled blasting can improve the degree of rock fragmentation, the average size of rock after blasting is smaller, more uniform particle size distribution. The research results for the control of blasting and optimization of explosive energy utilization have important reference significance.
{"title":"Study on fragmentation characteristics of rock mass in bench blasting with different coupling media","authors":"Tong Li, Ming Chen, Bo-wen Guo, Li Song, Bing Fan, Shan-shan Cui","doi":"10.3389/feart.2024.1445990","DOIUrl":"https://doi.org/10.3389/feart.2024.1445990","url":null,"abstract":"The fragmentation size distribution is an important index to evaluate blasting effect. Based on stress wave theory, a blasting fragmentation distribution model is established, and the key influencing factors were clarified. Then, the distribution characteristics of rock fragmentation in water-coupled blasting and air-coupled blasting were compared and verified by numerical simulation and field test. The results show that the rock blasting fragmentation size is negatively correlated with borehole pressure and unit explosive consumption when blasting rock is determined. The existence of water slows down the attenuation of blasting load, prolongs the duration, and makes the blasting pressure transmitted to hole wall significantly greater than air-coupled one, which is equivalent to increasing the unit explosive consumption. Moreover, the rock fracture development speed and fragmentation degree of water-coupled blasting is significantly higher than air-coupled blasting. Comprehensively determined in same charging parameters, water-coupled blasting compared with air-coupled blasting can improve the degree of rock fragmentation, the average size of rock after blasting is smaller, more uniform particle size distribution. The research results for the control of blasting and optimization of explosive energy utilization have important reference significance.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"42 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141880499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To refine the meteorological warning service for decision makers and enhance their role in disaster risk reduction, this paper puts forward the efficiency index for warning on disaster risk reduction by analyzing meteorological warnings. The influence factors of the index are investigated, and an index calculation model is established by using Grey relation analysis. The weights of the evaluation factors are determined by entropy weight method to quantify the efficiency of warning. Additionally, the reminder strength of different warning delivery methods to decision makers is studied, and a refined delivery strategy tree for warnings to decision makers is established based on the efficiency index and reminder strength of delivery means. The proposed strategy has been applied to the warning service system in Fujian Province. Results show that its implementation has improved the efficiency of warning dissemination and reduced delivery warning costs.
{"title":"Multidimensional evaluation and service strategy analysis of hazard warning and risk reduction","authors":"Zhiyu Cao, Jiahe Wang, Yingjie Liu, Jingjing Zhao, Yingying Song, Boting Zhao","doi":"10.3389/feart.2024.1362906","DOIUrl":"https://doi.org/10.3389/feart.2024.1362906","url":null,"abstract":"To refine the meteorological warning service for decision makers and enhance their role in disaster risk reduction, this paper puts forward the efficiency index for warning on disaster risk reduction by analyzing meteorological warnings. The influence factors of the index are investigated, and an index calculation model is established by using Grey relation analysis. The weights of the evaluation factors are determined by entropy weight method to quantify the efficiency of warning. Additionally, the reminder strength of different warning delivery methods to decision makers is studied, and a refined delivery strategy tree for warnings to decision makers is established based on the efficiency index and reminder strength of delivery means. The proposed strategy has been applied to the warning service system in Fujian Province. Results show that its implementation has improved the efficiency of warning dissemination and reduced delivery warning costs.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"68 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141880501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.3389/feart.2024.1404133
Yuanyue Pi, Zhong Sun, Yangyang Lu, Jian Xu
Tunnel water inrush may not only cause hundreds of millions of economic losses and serious casualties, but also leads to a series of ecological and environmental problems such as the decline of groundwater level, soil salinization and surface vegetation degradation. In this study, considering hydrogeology, construction, and dynamic monitoring factors, a new risk prediction model of water inrush is proposed based on fuzzy mathematical theory. The element of novelty is that this approach comprehensively considers nonlinearity and randomness factors, and the index values, weights, and membership are expressed as interval numbers instead of constant values. The interval membership degree of each index is calculated by an improved sigmoid membership function (SMF). A coupling algorithm of improved analytic hierarchy process and entropy method is used to calculate the index weight. In addition, the Boolean matrix is introduced into the relative advantage analysis of the interval vector, and the final risk level of water inrush is determined by the ranking result. The proposed model is applied to the analysis of the water inrush risk in the Ka−Shuang 2 (KS2) tunnel in Xinjiang, China. The predicted results align well with the actual excavation results, which indicates that this novel model has high accuracy and reliability. Simultaneously, a risk management response mechanism for different risk levels of water inrush is discussed, which is expected to provide a new research perspective for risk control of other related projects and promote regional sustainable development.
{"title":"A novel model for risk prediction of water inrush and its application in a tunnel in Xinjiang, China","authors":"Yuanyue Pi, Zhong Sun, Yangyang Lu, Jian Xu","doi":"10.3389/feart.2024.1404133","DOIUrl":"https://doi.org/10.3389/feart.2024.1404133","url":null,"abstract":"Tunnel water inrush may not only cause hundreds of millions of economic losses and serious casualties, but also leads to a series of ecological and environmental problems such as the decline of groundwater level, soil salinization and surface vegetation degradation. In this study, considering hydrogeology, construction, and dynamic monitoring factors, a new risk prediction model of water inrush is proposed based on fuzzy mathematical theory. The element of novelty is that this approach comprehensively considers nonlinearity and randomness factors, and the index values, weights, and membership are expressed as interval numbers instead of constant values. The interval membership degree of each index is calculated by an improved sigmoid membership function (SMF). A coupling algorithm of improved analytic hierarchy process and entropy method is used to calculate the index weight. In addition, the Boolean matrix is introduced into the relative advantage analysis of the interval vector, and the final risk level of water inrush is determined by the ranking result. The proposed model is applied to the analysis of the water inrush risk in the Ka−Shuang 2 (KS2) tunnel in Xinjiang, China. The predicted results align well with the actual excavation results, which indicates that this novel model has high accuracy and reliability. Simultaneously, a risk management response mechanism for different risk levels of water inrush is discussed, which is expected to provide a new research perspective for risk control of other related projects and promote regional sustainable development.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"82 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141886646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Landslide disasters, due to their widespread distribution and clustered occurrences, pose a significant threat to human society. Rainfall is considered a primary triggering factor, and the frequent clustering of landslides underscores the importance of early warning systems for regional landslide disasters in preventing and mitigating rainfall-induced landslides. Research on early warning models is crucial for accurately predicting rainfall-induced landslides. However, traditional models face challenges such as the complexity of landslide causes, insufficient data, and limited analysis methods, resulting in low accuracy and inadequate precision. This study focuses on Fujian Province, China, proposing a four-step process for building a regional landslide early warning model based on machine learning. The process includes data integration and cleaning, sample set construction, model training and validation, and practical application. By integrating and cleaning the latest and most detailed data, a training sample set (15,589 samples) for the regional landslide disaster early warning model is established. Three machine learning algorithms—Random Forest, Multilayer Perceptron, and Convolutional Neural Network—are employed and compared, the evaluation results indicated that the RF-based warning model achieved an accuracy of 0.930–0.957 and an AUC value of 0.955. The CNN-based warning model demonstrated an accuracy of 0.945–0.948 with an AUC value of 0.940. The MLP-based warning model achieved an accuracy of 0.930–0.953 and an AUC value of 0.930. The results showed comparable accuracy metrics among the three models, with RF exhibiting a significant advantage in AUC values. Finally, the models are applied to the regional landslide disasters induced by heavy rainfall in Fujian Province on 5 August 2021. The results showed that in the binary classification warning strategy, the accuracy of the Random Forest and Convolutional Neural Network was 92.9%, while that of the Multilayer Perceptron was 85.8%, all performing well. In the multi-classification hierarchical warning strategy, the Random Forest excelled, while the performance of the Convolutional Neural Network and Multilayer Perceptron was relatively limited. The findings of this study contribute to valuable attempts in landslide disaster warning model research, with anticipated further improvements through the gradual accumulation of samples and practical application verification.
{"title":"A comparative study of regional rainfall-induced landslide early warning models based on RF、CNN and MLP algorithms","authors":"Yanhui Liu, Shiwei Ma, Lihao Dong, Ruihua Xiao, Junbao Huang, Pinggen Zhou","doi":"10.3389/feart.2024.1419421","DOIUrl":"https://doi.org/10.3389/feart.2024.1419421","url":null,"abstract":"Landslide disasters, due to their widespread distribution and clustered occurrences, pose a significant threat to human society. Rainfall is considered a primary triggering factor, and the frequent clustering of landslides underscores the importance of early warning systems for regional landslide disasters in preventing and mitigating rainfall-induced landslides. Research on early warning models is crucial for accurately predicting rainfall-induced landslides. However, traditional models face challenges such as the complexity of landslide causes, insufficient data, and limited analysis methods, resulting in low accuracy and inadequate precision. This study focuses on Fujian Province, China, proposing a four-step process for building a regional landslide early warning model based on machine learning. The process includes data integration and cleaning, sample set construction, model training and validation, and practical application. By integrating and cleaning the latest and most detailed data, a training sample set (15,589 samples) for the regional landslide disaster early warning model is established. Three machine learning algorithms—Random Forest, Multilayer Perceptron, and Convolutional Neural Network—are employed and compared, the evaluation results indicated that the RF-based warning model achieved an accuracy of 0.930–0.957 and an AUC value of 0.955. The CNN-based warning model demonstrated an accuracy of 0.945–0.948 with an AUC value of 0.940. The MLP-based warning model achieved an accuracy of 0.930–0.953 and an AUC value of 0.930. The results showed comparable accuracy metrics among the three models, with RF exhibiting a significant advantage in AUC values. Finally, the models are applied to the regional landslide disasters induced by heavy rainfall in Fujian Province on 5 August 2021. The results showed that in the binary classification warning strategy, the accuracy of the Random Forest and Convolutional Neural Network was 92.9%, while that of the Multilayer Perceptron was 85.8%, all performing well. In the multi-classification hierarchical warning strategy, the Random Forest excelled, while the performance of the Convolutional Neural Network and Multilayer Perceptron was relatively limited. The findings of this study contribute to valuable attempts in landslide disaster warning model research, with anticipated further improvements through the gradual accumulation of samples and practical application verification.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"36 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141886663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3389/feart.2024.1403504
Lei Zuo, Peng Zhang, Ya-qin Wang, Rui Liu
Sulfur forms an immiscible liquid upon saturation in magma, and sulfide droplets are commonly found in fresh mid-ocean ridge basalt (MORB). Scanning electron microscopy (SEM) analysis revealed that the fine-grained and weakly phyric MORB samples exhibited hypocrystalline to vitreous textures. Transmission electron microscopy (TEM) of MORB glasses exhibits nanoscale sulfide droplets (10–15 nm) with rounded shapes and smooth edges, showing crystalline and homogeneous composition. Elemental distribution included S, Fe, Cu, and Ni, while Si, Al, and O were lacking. Prior research clarified the immiscibility between sulfide and silicate melts, impacting the size distribution of sulfide droplets. This is the first report on nanoscale sulfide droplets within MORB glasses, and these results suggest that nanoscale sulfide droplets represent the initial phase of sulfide saturation. Such an insight may prove useful in understanding how siderophile and chalcophile elements behaved during sulfide crystallization. In addition, this study determines the immiscibility of sulfides and silicate melts that occur in the early nanometer stage. Therefore, it is speculated that immiscibility phenomena may occur in the nanometer stage during magma evolution.
{"title":"A discovery of nanoscale sulfide droplets in MORB glasses: implications for the immiscibility of sulfide and silicate melts","authors":"Lei Zuo, Peng Zhang, Ya-qin Wang, Rui Liu","doi":"10.3389/feart.2024.1403504","DOIUrl":"https://doi.org/10.3389/feart.2024.1403504","url":null,"abstract":"Sulfur forms an immiscible liquid upon saturation in magma, and sulfide droplets are commonly found in fresh mid-ocean ridge basalt (MORB). Scanning electron microscopy (SEM) analysis revealed that the fine-grained and weakly phyric MORB samples exhibited hypocrystalline to vitreous textures. Transmission electron microscopy (TEM) of MORB glasses exhibits nanoscale sulfide droplets (10–15 nm) with rounded shapes and smooth edges, showing crystalline and homogeneous composition. Elemental distribution included S, Fe, Cu, and Ni, while Si, Al, and O were lacking. Prior research clarified the immiscibility between sulfide and silicate melts, impacting the size distribution of sulfide droplets. This is the first report on nanoscale sulfide droplets within MORB glasses, and these results suggest that nanoscale sulfide droplets represent the initial phase of sulfide saturation. Such an insight may prove useful in understanding how siderophile and chalcophile elements behaved during sulfide crystallization. In addition, this study determines the immiscibility of sulfides and silicate melts that occur in the early nanometer stage. Therefore, it is speculated that immiscibility phenomena may occur in the nanometer stage during magma evolution.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"65 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Through the examination of calcite twins, this research outlines the tectonic development and paleo stress patterns of the Paleozoic Routshon complex situated in the southeastern segment of the Sanandaj–Sirjan zone, a hinterland region of the Zagros orogeny in southeastern Iran. The study of orogenic phase indicates that the deformation event affecting the southern sector of the Sanandaj-Sirjan zone aligns with the Cimmerian orogenic phase of the Late Triassic period. A variety of structural features at both map and outcrop scales highlight the importance of slip partitioning in the structural evolution of this region, driven by inclined transpression. Observations suggest that the deformation related to contractional components includes steeply to moderately plunging folds, dip-slip domain deformation primarily involving thrusts, and ongoing deformation by strike-slip component motion, which results in thrust-related ductile shear zones. The analysis of calcite c-axis fabrics from mylonite samples obtained from these shear zones indicates a low-temperature monoclinic pattern of non-coaxial deformation. This deformation type underscores the impact of the strike-slip component in the development of progressive simple shear within thrust-related shear zones in this segment of the Sanandaj-Sirjan zone. Dynamic analysis of c-axis fabric data reveals a NE-SW orientation for the principal compressive axes (σ1) in this area. This direction, corroborated by additional data such as fault surface, GPS, and earthquake focal mechanism data, confirms that the orientation of the compressive axes (σ1) has remained consistent from the Late Triassic to the present.
本研究通过对方解石孪晶的研究，概述了位于伊朗东南部扎格罗斯造山带腹地萨南达季-锡尔詹地区东南段的古生代鲁特松复合体的构造发展和古应力模式。对造山运动相位的研究表明，影响萨南达季-锡尔詹带南段的变形事件与晚三叠世时期的西梅利亚造山运动相位一致。地图和露头尺度上的各种结构特征突出表明，在倾斜换位的驱动下，滑移分区在该地区结构演变中的重要性。观察结果表明，与收缩成分有关的变形包括陡峭至中等程度的褶皱、主要涉及推力的倾覆滑动域变形，以及由走向滑动成分运动引起的持续变形，这导致了与推力有关的韧性剪切带。对从这些剪切带获得的麦饭石样本中的方解石 c 轴结构进行的分析表明，非同轴变形的低温单斜模式。这种变形类型凸显了在萨南达季-锡尔詹区段与推力相关的剪切带中，走向滑动成分对渐进式简单剪切发展的影响。对 c 轴结构数据的动态分析显示，该地区的主要压缩轴（σ1）呈东北-西南走向。这一方向与断层面、全球定位系统和地震焦点机制数据等其他数据相印证，证实了压缩轴（σ1）的方向从三叠纪晚期至今一直保持一致。
{"title":"Calcite e-twins as a tectonic indicator, paleo stress pattern and structural evolution of the Zagros hinterland, SE Iran","authors":"Hamed Dorzadeh, Shahram Shafieibafti, Saeede Keshavarz, Jafar Omrani, Ahmad Rashidi, Majid Nemati, Reza Derakhshani","doi":"10.3389/feart.2024.1445918","DOIUrl":"https://doi.org/10.3389/feart.2024.1445918","url":null,"abstract":"Through the examination of calcite twins, this research outlines the tectonic development and paleo stress patterns of the Paleozoic Routshon complex situated in the southeastern segment of the Sanandaj–Sirjan zone, a hinterland region of the Zagros orogeny in southeastern Iran. The study of orogenic phase indicates that the deformation event affecting the southern sector of the Sanandaj-Sirjan zone aligns with the Cimmerian orogenic phase of the Late Triassic period. A variety of structural features at both map and outcrop scales highlight the importance of slip partitioning in the structural evolution of this region, driven by inclined transpression. Observations suggest that the deformation related to contractional components includes steeply to moderately plunging folds, dip-slip domain deformation primarily involving thrusts, and ongoing deformation by strike-slip component motion, which results in thrust-related ductile shear zones. The analysis of calcite c-axis fabrics from mylonite samples obtained from these shear zones indicates a low-temperature monoclinic pattern of non-coaxial deformation. This deformation type underscores the impact of the strike-slip component in the development of progressive simple shear within thrust-related shear zones in this segment of the Sanandaj-Sirjan zone. Dynamic analysis of c-axis fabric data reveals a NE-SW orientation for the principal compressive axes (σ1) in this area. This direction, corroborated by additional data such as fault surface, GPS, and earthquake focal mechanism data, confirms that the orientation of the compressive axes (σ1) has remained consistent from the Late Triassic to the present.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"2 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3389/feart.2024.1379870
Jinxiu Yu
Introductions: Since the reform and opening up, the inflow of foreign direct investment (FDI) has provided a steady stream of capital, technology, talent and other resources for the development of the Yellow River basin, while caused problems such as environmental pollution, ecological fragility and industrial structure upgrading difficulties to some extent. Environmental regulation is a pivotal initiative to achieve mutual harmony between ecological environment and economic development, which could enhance the quality of the introduction of FDI and accelerate the green transformation of the development mode.Methods: Based on urban panel data from 2006–2019, this study empirically examined the impact of FDI and environmental regulation on industrial structure upgrading in the Yellow River Basin. Moreover, taking environmental regulation as a threshold variable, a panel threshold model was established to further explore the role of environmental regulation in the impact of FDI on industrial structure upgrading in the Yellow River Basin.Results: (1) The relationship between FDI and industrial structure upgrading in the Yellow River Basin is not a simple linear relationship, but an inverted “U”-shaped relationship that rises first and then falls, and the results of this inverted “U”-shaped relationship are still robust after replacing key indicators. (2) The environmental regulation policy has a driving effect on the upgrading of industrial structure in the Yellow River Basin. (3) Environmental regulation has a positive role in the influence of FDI on the industrial structure upgrading in the Yellow River basin, and the positive role increases gradually as the intensity of environmental regulation increases moderately, but if the intensity of environmental regulation is too high, it will have a negative impact on the upgrading of industrial structure in the Yellow River basin to some extent.Discussion: In the future, policymakers should make reasonable and effective use of FDI and improve the quality of FDI; reasonably formulate environmental regulation policies; coordinate the intensity of FDI and environmental regulation; thus, bring into play the promotion effect of FDI and environmental regulation on industrial structure upgrading, and then realize the win-win of ecological protection and high-quality economic development in the Yellow River Basin.
{"title":"Research on the impact of FDI and environmental regulation on the industrial structure upgrading in the Yellow River Basin","authors":"Jinxiu Yu","doi":"10.3389/feart.2024.1379870","DOIUrl":"https://doi.org/10.3389/feart.2024.1379870","url":null,"abstract":"Introductions: Since the reform and opening up, the inflow of foreign direct investment (FDI) has provided a steady stream of capital, technology, talent and other resources for the development of the Yellow River basin, while caused problems such as environmental pollution, ecological fragility and industrial structure upgrading difficulties to some extent. Environmental regulation is a pivotal initiative to achieve mutual harmony between ecological environment and economic development, which could enhance the quality of the introduction of FDI and accelerate the green transformation of the development mode.Methods: Based on urban panel data from 2006–2019, this study empirically examined the impact of FDI and environmental regulation on industrial structure upgrading in the Yellow River Basin. Moreover, taking environmental regulation as a threshold variable, a panel threshold model was established to further explore the role of environmental regulation in the impact of FDI on industrial structure upgrading in the Yellow River Basin.Results: (1) The relationship between FDI and industrial structure upgrading in the Yellow River Basin is not a simple linear relationship, but an inverted “U”-shaped relationship that rises first and then falls, and the results of this inverted “U”-shaped relationship are still robust after replacing key indicators. (2) The environmental regulation policy has a driving effect on the upgrading of industrial structure in the Yellow River Basin. (3) Environmental regulation has a positive role in the influence of FDI on the industrial structure upgrading in the Yellow River basin, and the positive role increases gradually as the intensity of environmental regulation increases moderately, but if the intensity of environmental regulation is too high, it will have a negative impact on the upgrading of industrial structure in the Yellow River basin to some extent.Discussion: In the future, policymakers should make reasonable and effective use of FDI and improve the quality of FDI; reasonably formulate environmental regulation policies; coordinate the intensity of FDI and environmental regulation; thus, bring into play the promotion effect of FDI and environmental regulation on industrial structure upgrading, and then realize the win-win of ecological protection and high-quality economic development in the Yellow River Basin.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"57 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3389/feart.2024.1434820
Anupam Yadav, Saeed Hameed Aldulaimi, Farag M. A. Altalbawy, Praveen K. N. Raja, M. Janaki Ramudu, Nizomiddin Juraev, Hameed Hassan Khalaf, Bassam Farman Bassam, Nada Qasim Mohammed, Dunya Jameel Kassid, Ahmed Elawady, Mohammad Sina
The most widely used equation to calculate water saturation or suitable shaly water saturation in clean or shaly formation, respectively, is the modified Archie formula. The quality of Archie parameters including saturation exponent affects the preciseness of water saturation, and thus estimated oil and gas in place. Therefore, estimating the saturation exponent by the soft computation methods deems to be necessary. In this study, intelligent models such as multilayer perceptron neural network, least squares support vector machine, radial basis function neural network, and adaptive neuro-fuzzy inference system are developed to predict saturation exponent in terms of petrophysical data including porosity, absolute permeability, water saturation, true resistivity, and resistivity index by utilizing a databank for middle east oil and gas reservoirs. The introduced models are optimized using particle swarm optimization, genetic algorithm, and levenberg marquardt techniques. Graphical and statistical methods are used to demonstrate the capability of the constructed models. Based on the statistical indexes obtained for each model, it is found that radial basis function neural network, multilayer perceptron neural network, and least squares support vector machine are the most robust models as they possess the smallest mean squared error, root mean squared error and average absolute relative error as well as highest coefficient of determination. Moreover, the sensitivity analysis indicates that water saturation has the most effect and porosity has the least effect on the saturation exponent. The developed models are simple-to-use and time-consuming tools to predict saturation exponent without needing laboratory methods which are tedious and arduous.
{"title":"Prediction of saturation exponent for subsurface oil and gas reservoirs using soft computing methods","authors":"Anupam Yadav, Saeed Hameed Aldulaimi, Farag M. A. Altalbawy, Praveen K. N. Raja, M. Janaki Ramudu, Nizomiddin Juraev, Hameed Hassan Khalaf, Bassam Farman Bassam, Nada Qasim Mohammed, Dunya Jameel Kassid, Ahmed Elawady, Mohammad Sina","doi":"10.3389/feart.2024.1434820","DOIUrl":"https://doi.org/10.3389/feart.2024.1434820","url":null,"abstract":"The most widely used equation to calculate water saturation or suitable shaly water saturation in clean or shaly formation, respectively, is the modified Archie formula. The quality of Archie parameters including saturation exponent affects the preciseness of water saturation, and thus estimated oil and gas in place. Therefore, estimating the saturation exponent by the soft computation methods deems to be necessary. In this study, intelligent models such as multilayer perceptron neural network, least squares support vector machine, radial basis function neural network, and adaptive neuro-fuzzy inference system are developed to predict saturation exponent in terms of petrophysical data including porosity, absolute permeability, water saturation, true resistivity, and resistivity index by utilizing a databank for middle east oil and gas reservoirs. The introduced models are optimized using particle swarm optimization, genetic algorithm, and levenberg marquardt techniques. Graphical and statistical methods are used to demonstrate the capability of the constructed models. Based on the statistical indexes obtained for each model, it is found that radial basis function neural network, multilayer perceptron neural network, and least squares support vector machine are the most robust models as they possess the smallest mean squared error, root mean squared error and average absolute relative error as well as highest coefficient of determination. Moreover, the sensitivity analysis indicates that water saturation has the most effect and porosity has the least effect on the saturation exponent. The developed models are simple-to-use and time-consuming tools to predict saturation exponent without needing laboratory methods which are tedious and arduous.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"10 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To clarify the influence range and saturation distribution after the biogas desaturation method is applied, a three-dimensional model is established with TOUGH2 software to analyze the effect of construction parameters such as grouting volume, grouting rate, grouting depth, nitrogen source concentration, and soil porosity. After that, the sensitivity of the parameters on the influence range is determined. The grouting volume and soil porosity are the most sensitive to the lateral and vertical influence range, respectively. This study provides a basis for the engineering practice of treating liquefiable subgrade by the biogas desaturation method.
{"title":"The influence range of the biogas desaturation method for mitigating sand liquefaction","authors":"Erxing Peng, Dandan Li, Xiaoying Hu, Binbin He, Haiming Dang, Youqian Liu","doi":"10.3389/feart.2024.1433507","DOIUrl":"https://doi.org/10.3389/feart.2024.1433507","url":null,"abstract":"To clarify the influence range and saturation distribution after the biogas desaturation method is applied, a three-dimensional model is established with TOUGH2 software to analyze the effect of construction parameters such as grouting volume, grouting rate, grouting depth, nitrogen source concentration, and soil porosity. After that, the sensitivity of the parameters on the influence range is determined. The grouting volume and soil porosity are the most sensitive to the lateral and vertical influence range, respectively. This study provides a basis for the engineering practice of treating liquefiable subgrade by the biogas desaturation method.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"72 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3389/feart.2024.1421404
Pengyan Du, Jingong Cai, Huidong Li, Xuejun Zhang, Juan Wang, Liping Yang, Yanzhong Zhen
Whether mudstone is rich in or free of organic matter has a great influence on the occurrence of water. Comparing different types of water in organic-rich and organic-free mudstones is helpful for further understanding the role of water in hydrocarbon generation. Thermogravimetric analysis (TGA) and differential thermal analysis (DTA) combined with mass spectrometry (MS) afford the opportunity to identify the mass change, reactions and products of the sample in a real-time monitored heating process. This study compared the pyrolysis characteristics of an organic-rich mudstone (CN1) and an organic-free mudstone (CW1) by using the TGA/DTA-MS method to estimate the content of different types of H2O and CO2 in organic-rich mudstones. The results show that the mass changes in CN1 and CW1 can be divided into the three thermogravimetric (TG) stages of 0°C–200°C, 200°C–650°C, and 650°C–900°C, while the peak temperatures of H2O and CO2 obtained through MS are different for CN1 and CW1. The differences in mineral components and organic matter between CN1 and CW1 suggest that the MS peaks of H2O and CO2 in CW1 are mainly influenced by clay and carbonate minerals, and that those of CN1 are also influenced by organic matter. In addition, quantification equations for CO2 and H2O contents from both the organic and inorganic origin of the organic-rich mudstone can be established by using the MS peak area of CO2 and H2O, mass loss in TGA and the mineral composition of the organic-free mudstone. This work provides useful insights for further understanding the hydrocarbon generation mechanism, as well as quantifying different types of water in organic-rich mudstones.
泥岩富含或不含有机物对水的出现有很大影响。比较富含有机物和不含有机物泥岩中不同类型的水有助于进一步了解水在碳氢化合物生成过程中的作用。热重分析法（TGA）和差热分析法（DTA）与质谱法（MS）相结合，可在实时监测的加热过程中确定样品的质量变化、反应和产物。本研究利用 TGA/DTA-MS 方法比较了富含有机质的泥岩（CN1）和不含有机质的泥岩（CW1）的热解特征，以估算富含有机质的泥岩中不同类型的 H2O 和 CO2 的含量。结果表明，CN1 和 CW1 的质量变化可分为 0°C-200°C、200°C-650°C 和 650°C-900°C三个热重（TG）阶段，而通过 MS 获得的 H2O 和 CO2 的峰值温度在 CN1 和 CW1 中是不同的。CN1 和 CW1 在矿物成分和有机物方面的差异表明，CW1 中 H2O 和 CO2 的 MS 峰值主要受粘土和碳酸盐矿物的影响，而 CN1 中的 H2O 和 CO2 峰值也受有机物的影响。此外，利用 CO2 和 H2O 的 MS 峰面积、TGA 中的质量损失以及无机泥岩的矿物组成，可以建立富有机泥岩中有机和无机来源的 CO2 和 H2O 含量的量化方程。这项工作为进一步了解碳氢化合物的生成机制以及量化富含有机质泥岩中不同类型的水提供了有益的启示。
{"title":"Quantification of organic and inorganic hydrogen in mudstones: a novel approach using the difference between organic-rich and organic-free mudstones during pyrolysis process","authors":"Pengyan Du, Jingong Cai, Huidong Li, Xuejun Zhang, Juan Wang, Liping Yang, Yanzhong Zhen","doi":"10.3389/feart.2024.1421404","DOIUrl":"https://doi.org/10.3389/feart.2024.1421404","url":null,"abstract":"Whether mudstone is rich in or free of organic matter has a great influence on the occurrence of water. Comparing different types of water in organic-rich and organic-free mudstones is helpful for further understanding the role of water in hydrocarbon generation. Thermogravimetric analysis (TGA) and differential thermal analysis (DTA) combined with mass spectrometry (MS) afford the opportunity to identify the mass change, reactions and products of the sample in a real-time monitored heating process. This study compared the pyrolysis characteristics of an organic-rich mudstone (CN1) and an organic-free mudstone (CW1) by using the TGA/DTA-MS method to estimate the content of different types of H<jats:sub>2</jats:sub>O and CO<jats:sub>2</jats:sub> in organic-rich mudstones. The results show that the mass changes in CN1 and CW1 can be divided into the three thermogravimetric (TG) stages of 0°C–200°C, 200°C–650°C, and 650°C–900°C, while the peak temperatures of H<jats:sub>2</jats:sub>O and CO<jats:sub>2</jats:sub> obtained through MS are different for CN1 and CW1. The differences in mineral components and organic matter between CN1 and CW1 suggest that the MS peaks of H<jats:sub>2</jats:sub>O and CO<jats:sub>2</jats:sub> in CW1 are mainly influenced by clay and carbonate minerals, and that those of CN1 are also influenced by organic matter. In addition, quantification equations for CO<jats:sub>2</jats:sub> and H<jats:sub>2</jats:sub>O contents from both the organic and inorganic origin of the organic-rich mudstone can be established by using the MS peak area of CO<jats:sub>2</jats:sub> and H<jats:sub>2</jats:sub>O, mass loss in TGA and the mineral composition of the organic-free mudstone. This work provides useful insights for further understanding the hydrocarbon generation mechanism, as well as quantifying different types of water in organic-rich mudstones.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":"56 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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