In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geo...In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.展开更多
CO_(2)+O_(2) in-situ leaching(ISL)of sandstonetype uranium ore represents the third generation of solution mining in China.In this study,reactive transport modeling of the interaction between hydrodynamic and geochemi...CO_(2)+O_(2) in-situ leaching(ISL)of sandstonetype uranium ore represents the third generation of solution mining in China.In this study,reactive transport modeling of the interaction between hydrodynamic and geochemical reactions is performed to enable better prediction and regulation of the CO_(2)+O_(2) in-situ leaching process of uranium.Geochemical reactions between mining solutions and rock,and the kinetic uranium dissolution controlled by O_(2)(aq)and bicarbonate(HCO_(3)-)are considered in the CO_(2)+O_(2) ISL reactive transport model of a typical sandstone-hosted uranium ore deposit in northern China.The reactive leaching of uranium is most sensitive to the spatial distribution of the mineralogical properties of the uranium deposit.Stochastic geostatistical models are used to represent the uncertainty on the spatial distribution of mineral grades.A Monte Carlo analysis was also performed to simulate the uranium production variability over an entire set of geostatistical realizations.The ISL stochastic simulation performed with the selected geostatistical realizations approximates the uranium production variability well.The simulation results of the ISL reactive transport model show that the extent of the uranium plume is highly dependent on mineralogical heterogeneity.The uncertainty analysis suggests the effect of uranium grade heterogeneity was found to be important to improve the accurate capture of the uncertainty.This study provides guidance for the accurate simulation and dynamic regulation of the CO_(2)+O_(2) leaching process of uranium at the scale of large mining areas.展开更多
National-level climate action plans are often formulated broadly. Spatially disaggregating these plans to individual municipalities can offer substantial benefits, such as enabling regional climate action strategies a...National-level climate action plans are often formulated broadly. Spatially disaggregating these plans to individual municipalities can offer substantial benefits, such as enabling regional climate action strategies and for assessing the feasibility of national objectives. Numerous spatial disaggregation approaches can be found in the literature. This study reviews and categorizes these. The review is followed by a discussion of the relevant methods for the disaggregation of climate action plans. It is seen that methods employing proxy data, machine learning models, and geostatistical ones are the most relevant methods for the spatial disaggregation of national energy and climate plans. The analysis offers guidance for selecting appropriate methods based on factors such as data availability at the municipal level and the presence of spatial autocorrelation in the data.As the urgency of addressing climate change escalates, understanding the spatial aspects of national energy and climate strategies becomes increasingly important. This review will serve as a valuable guide for researchers and practitioners applying spatial disaggregation in this crucial field.展开更多
文摘In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.
基金jointly supported by the National Key Research and Development Program of China(No.2019YFC1804304)the National Natural Science Foundation of China(Nos.2167212,41772254)。
文摘CO_(2)+O_(2) in-situ leaching(ISL)of sandstonetype uranium ore represents the third generation of solution mining in China.In this study,reactive transport modeling of the interaction between hydrodynamic and geochemical reactions is performed to enable better prediction and regulation of the CO_(2)+O_(2) in-situ leaching process of uranium.Geochemical reactions between mining solutions and rock,and the kinetic uranium dissolution controlled by O_(2)(aq)and bicarbonate(HCO_(3)-)are considered in the CO_(2)+O_(2) ISL reactive transport model of a typical sandstone-hosted uranium ore deposit in northern China.The reactive leaching of uranium is most sensitive to the spatial distribution of the mineralogical properties of the uranium deposit.Stochastic geostatistical models are used to represent the uncertainty on the spatial distribution of mineral grades.A Monte Carlo analysis was also performed to simulate the uranium production variability over an entire set of geostatistical realizations.The ISL stochastic simulation performed with the selected geostatistical realizations approximates the uranium production variability well.The simulation results of the ISL reactive transport model show that the extent of the uranium plume is highly dependent on mineralogical heterogeneity.The uncertainty analysis suggests the effect of uranium grade heterogeneity was found to be important to improve the accurate capture of the uncertainty.This study provides guidance for the accurate simulation and dynamic regulation of the CO_(2)+O_(2) leaching process of uranium at the scale of large mining areas.
基金funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No.101036458.
文摘National-level climate action plans are often formulated broadly. Spatially disaggregating these plans to individual municipalities can offer substantial benefits, such as enabling regional climate action strategies and for assessing the feasibility of national objectives. Numerous spatial disaggregation approaches can be found in the literature. This study reviews and categorizes these. The review is followed by a discussion of the relevant methods for the disaggregation of climate action plans. It is seen that methods employing proxy data, machine learning models, and geostatistical ones are the most relevant methods for the spatial disaggregation of national energy and climate plans. The analysis offers guidance for selecting appropriate methods based on factors such as data availability at the municipal level and the presence of spatial autocorrelation in the data.As the urgency of addressing climate change escalates, understanding the spatial aspects of national energy and climate strategies becomes increasingly important. This review will serve as a valuable guide for researchers and practitioners applying spatial disaggregation in this crucial field.
