Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to...Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to summarize the environmental sensitive variables for soil electrical conductivity(EC) estimation systematically. Additionally, the performance of Multiple Linear Regression(MLR), Geographically Weighted Regression(GWR), and Random Forest regression(RFR) model, the representative of current main methods for soil EC prediction, has not been explored. Taking the north of Yinchuan plain irrigation oasis as the study area, the feasibility and potential of 64 environmental variables, extracted from the Landsat 8 remote sensed images in dry season and wet season, the digital elevation model, and other data, were assessed through the correlation analysis and the performance of MLR, GWR, and RFR model on soil salinity estimation was compared. The results showed that: 1) 10 of 15 imagery texture and spectral band reflectivity environmental variables extracted from Landsat 8 image in dry season were significantly correlated with soil EC, while only 3 of these indices extracted from Landsat 8 image in wet season have significant correlation with soil EC. Channel network base level, one of the terrain attributes, had the largest absolute correlation coefficient of 0.47 and all spatial location factors had significant correlation with soil EC. 2) Prediction accuracy of RFR model was slightly higher than that of the GWR model, while MLR model produced the largest error. 3) In general, the soil salinization level in the study area gradually increased from south to north. In conclusion, the remote sensed imagery scanned in dry season was more suitable for soil EC estimation, and topographic factors and spatial location also play a key role. This study can contribute to the research on model construction and variables selection for soil salinity estimation in arid and semiarid regions.展开更多
A catalyst of ferroelectric-BaTiO_(3)@photoelectric-TiO_(2) nanohybrids(BaTiO_(3)@TiO_(2))with enhanced photocatalytic activity was synthesized via a hydrolysis precipitation combined with a hydrothermal approach.Comp...A catalyst of ferroelectric-BaTiO_(3)@photoelectric-TiO_(2) nanohybrids(BaTiO_(3)@TiO_(2))with enhanced photocatalytic activity was synthesized via a hydrolysis precipitation combined with a hydrothermal approach.Compared to pure TiO_(2),pure BaTiO_(3) and BaTiO_(3)/TiO_(2) physical mixture,the heterostructured BaTiO_(3)@TiO_(2) exhibits significantly improved photocatalytic activity and cycling stability in decomposing Rhodamine B(RhB)and the degradation efficiency is 1.7 times higher than pure TiO_(2) and 7.2 times higher than pure BaTiO_(3).These results are mainly attributed to the synergy effect of photoelectric TiO_(2),ferroelectric-BaTiO_(3) and the rationally designed interfacial structure.The mesoporous microstructure of TiO_(2) is of a high specific area and enables excellent photocatalytic activity.The ferroelectric polarization induced built-in electric field in BaTiO_(3) nanoparticles,and the intimate interfacial interactions at the interface of BaTiO_(3) and TiO_(2) are effective in driving the separation and transport of photogenerated charge carriers.This strategy will stimulate the design of heterostructured photocatalysts with outstanding photocatalytic performance via interface engineering.展开更多
Determining the distributions and sources of heavy metals in soils and assessing ecological risks are fundamental tasks in the control and management of pollution in mining areas.In this study,we selected 244 sampling...Determining the distributions and sources of heavy metals in soils and assessing ecological risks are fundamental tasks in the control and management of pollution in mining areas.In this study,we selected 244 sampling sites around a typical lead(Pb)and zinc(Zn)mining area in eastern Inner Mongolia Autonomous Region of China and measured the content of six heavy metals,including cuprum(Cu),Zn,Pb,arsenic(As),cadmium(Cd),and chromium(Cr).The ecological risk of heavy metals was comprehensively evaluated using the Geo-accumulation index,Nemerow general pollution index,and potential ecological risk index.The heavy metals were traced using correlation analysis and principal component analysis.The results showed that the highest content of heavy metals was found in 0–5 cm soil layer in the study area.The average content of Zn,As,Pb,Cu,Cr,and Cd was 670,424,235,162,94,and 4 mg/kg,respectively,all exceeding the risk screening value of agricultural soil in China.The areas with high content of soil heavy metals were mainly distributed near the tailings pond.The study area was affected by a combination of multiple heavy metals,with Cd and As reaching severe pollution levels.The three pathways of exposure for carcinogenic and noncarcinogenic risks were ranked as inhalation>oral ingestion>dermal absorption.The heavy metals in the study area posed certain hazards to human health.Specifically,oral ingestion of these heavy metals carried carcinogenic risks for both children and adults,as well as noncarcinogenic risks for children.There were differences in the sources of different heavy metals.The tailings pond had a large impact on the accumulation of Cd,Zn,and Pb.The source of Cr was the soil parent material,the source of As was mainly the soil matrix,and the source of Cu was mainly the nearby Cu ore.The purpose of this study is to more accurately understand the extent,scope,and source of heavy metals pollution near a typical mining area,providing effective help to solve the problem of heavy metals pollution.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41571217)National Program on Key Basic Research Project(No.2016YFD0300801)
文摘Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to summarize the environmental sensitive variables for soil electrical conductivity(EC) estimation systematically. Additionally, the performance of Multiple Linear Regression(MLR), Geographically Weighted Regression(GWR), and Random Forest regression(RFR) model, the representative of current main methods for soil EC prediction, has not been explored. Taking the north of Yinchuan plain irrigation oasis as the study area, the feasibility and potential of 64 environmental variables, extracted from the Landsat 8 remote sensed images in dry season and wet season, the digital elevation model, and other data, were assessed through the correlation analysis and the performance of MLR, GWR, and RFR model on soil salinity estimation was compared. The results showed that: 1) 10 of 15 imagery texture and spectral band reflectivity environmental variables extracted from Landsat 8 image in dry season were significantly correlated with soil EC, while only 3 of these indices extracted from Landsat 8 image in wet season have significant correlation with soil EC. Channel network base level, one of the terrain attributes, had the largest absolute correlation coefficient of 0.47 and all spatial location factors had significant correlation with soil EC. 2) Prediction accuracy of RFR model was slightly higher than that of the GWR model, while MLR model produced the largest error. 3) In general, the soil salinization level in the study area gradually increased from south to north. In conclusion, the remote sensed imagery scanned in dry season was more suitable for soil EC estimation, and topographic factors and spatial location also play a key role. This study can contribute to the research on model construction and variables selection for soil salinity estimation in arid and semiarid regions.
基金Project(cstc2020jcyj-msxm X0930) supported by the Natural Science Foundation of Chongqing,ChinaProject(KJQN201901522) supported by Technological Research Program of Chongqing Municipal Education Commission,ChinaProject(cx2020068) supported by the Venture&Innovation Support Program for Chongqing Overseas Returnees,China。
文摘A catalyst of ferroelectric-BaTiO_(3)@photoelectric-TiO_(2) nanohybrids(BaTiO_(3)@TiO_(2))with enhanced photocatalytic activity was synthesized via a hydrolysis precipitation combined with a hydrothermal approach.Compared to pure TiO_(2),pure BaTiO_(3) and BaTiO_(3)/TiO_(2) physical mixture,the heterostructured BaTiO_(3)@TiO_(2) exhibits significantly improved photocatalytic activity and cycling stability in decomposing Rhodamine B(RhB)and the degradation efficiency is 1.7 times higher than pure TiO_(2) and 7.2 times higher than pure BaTiO_(3).These results are mainly attributed to the synergy effect of photoelectric TiO_(2),ferroelectric-BaTiO_(3) and the rationally designed interfacial structure.The mesoporous microstructure of TiO_(2) is of a high specific area and enables excellent photocatalytic activity.The ferroelectric polarization induced built-in electric field in BaTiO_(3) nanoparticles,and the intimate interfacial interactions at the interface of BaTiO_(3) and TiO_(2) are effective in driving the separation and transport of photogenerated charge carriers.This strategy will stimulate the design of heterostructured photocatalysts with outstanding photocatalytic performance via interface engineering.
基金supported by the Inner Mongolia Autonomous Region Major Science and Technology Special Project (2019ZD001).
文摘Determining the distributions and sources of heavy metals in soils and assessing ecological risks are fundamental tasks in the control and management of pollution in mining areas.In this study,we selected 244 sampling sites around a typical lead(Pb)and zinc(Zn)mining area in eastern Inner Mongolia Autonomous Region of China and measured the content of six heavy metals,including cuprum(Cu),Zn,Pb,arsenic(As),cadmium(Cd),and chromium(Cr).The ecological risk of heavy metals was comprehensively evaluated using the Geo-accumulation index,Nemerow general pollution index,and potential ecological risk index.The heavy metals were traced using correlation analysis and principal component analysis.The results showed that the highest content of heavy metals was found in 0–5 cm soil layer in the study area.The average content of Zn,As,Pb,Cu,Cr,and Cd was 670,424,235,162,94,and 4 mg/kg,respectively,all exceeding the risk screening value of agricultural soil in China.The areas with high content of soil heavy metals were mainly distributed near the tailings pond.The study area was affected by a combination of multiple heavy metals,with Cd and As reaching severe pollution levels.The three pathways of exposure for carcinogenic and noncarcinogenic risks were ranked as inhalation>oral ingestion>dermal absorption.The heavy metals in the study area posed certain hazards to human health.Specifically,oral ingestion of these heavy metals carried carcinogenic risks for both children and adults,as well as noncarcinogenic risks for children.There were differences in the sources of different heavy metals.The tailings pond had a large impact on the accumulation of Cd,Zn,and Pb.The source of Cr was the soil parent material,the source of As was mainly the soil matrix,and the source of Cu was mainly the nearby Cu ore.The purpose of this study is to more accurately understand the extent,scope,and source of heavy metals pollution near a typical mining area,providing effective help to solve the problem of heavy metals pollution.
