Rapid estimation of soil heavy metal nickel content based on optimized screening of near-infrared spectral bands

In near-infrared spectroscopy,the traditional feature band extraction method has certain limitations.Therefore,a band extraction method named the three-step extraction method was proposed.This method combines characteristic absorption bands and correlation coefficients to select characteristic bands corresponding to various spectral forms and then uses stepwise regression to eliminate meaningless variables.Partial least squares regression(PLSR)and extreme learning machine(ELM)models were used to verify the effect of the band extraction method.Results show that the differential transformation of the spectrum can effectively improve the correlation between the spectrum and nickel(Ni)content.Most correlation coefficients were above 0.7 and approximately 20%higher than those of other transformation methods.The model effect established by the feature variable selection method based on comprehensive spectral transformation is only slightly affected by the spectral transformation form.Infive types of spectral transformation,the RPD values of the proposed method were all within the same level.The RPD values of the PLSR model were concentrated between 1.6 and 1.8,and those of the ELM model were between 2.5 and2.9,indicating that this method is beneficial for extracting more complete spectral features.The combination of the three-step extraction method and ELM algorithm can effectively retain important bands associated with the Ni content of the soil.The model based on the spectral band selected by the three-step extraction method has better prediction ability than the other models.The ELM model of the first-order differential transformation has the best prediction accuracy(RP^2=0.923,RPD=3.634).The research results provide some technical support for monitoring heavy metal content spectrum in local soils.

Hyperspectral estimation model of soil Pb content and its applicability in different soil types

In order to obtain Pb content in soil quickly and efficiently,a multivariate linear regression(MLR) and a principal component regression(PCR) Pb content estimation model were established on the basis of hyperspectral techniques,and their applicability in different soil types was evaluated.Results indicated that Pb exhibited strong spatial heterogeneity in the study area,and more than 82% of the samples exceeded the background value.In addition,the pollution range was large.Pb was sensitive in the nearinfrared band,and the correlation of absorbance(AB) was most significant of all the transformed forms.Both models achieved optimal stability and reliability when AB was used as an independent variable.Compared with the PCR model,the stability,fitting accuracy,and predictive power of the MLR model were superior with a coefficient of determination,root mean square error,and mean relative error of 0.724%,24.92%,and 28.22%,respectively.Both models could be applied to different soil types;however,MLR had better applicability compared with PCR.The PCR model that distinguished different soil types had better reliability than one that did not.Thus,the model established via hyperspectral techniques can achieve largearea,rapid,and efficient soil Pb content monitoring,which can provide technical support for the treatment of heavy metal pollution in soil.

Dual-filler reinforced PVDF-HFP based polymer electrolyte enabling high-safety design of lithium metal batteries

Despite the high energy density of lithium metal batteries(LMBs),their application in rechargeable batteries is still hampered due to insufficient safety.Here,we present a novel flame-retardant solid-state electrolyte based on polyvinylidene fluoride-hexafluoropropylene(PVDF-HFP)with nano SiO_(2)aerogel as an inert filler but Li_(6.4)La_(3)Zr_(1.4)Ta_(0.6)O_(12)(LLZTO)as an auxiliary component to enhance the ion conductivity.The introduction of SiO_(2)aerogels imparts the polymer electrolyte with exceptional thermal stability and flame retardancy.Simultaneously,the interaction between hydroxyl groups of SiO_(2)particles and PVDF-HFP creates a strong cross-linking structure,enhancing the mechanical strength and stability of the electrolyte.Furthermore,the presence of SiO_(2)aerogel and LLZTO facilitates the dissociation of lithium salts through Lewis acid-base interactions,resulting in a high ionic conductivity of 1.01×10^(−3)S·cm^(−1)and a wide electrochemical window of~5.0 V at room temperature for the prepared electrolytes.Remarkably,the assembled Li|Li cell demonstrates the excellent resistance to lithium dendrite and runs stablly for over 1500 h at a current density of 0.25 mA·cm^(−2).Thus,we prepare a pouch cell with high safety,which can work normally after short-circuiting under the external folding and cutting.

Global patterns and changes of carbon emissions from land use during 1992e2015

Carbon emissions from land use(ELUC)are an important part of anthropogenic CO_(2) emissions,but its size and location remain uncertain,and our knowledge of the relationship between ELUC and GDP remains partial.We showed that the carbon emissions directly caused by land use change(direct ELUC)during 1992-2015 was 26.54 Pg C(1.15 Pg C yr^(-1)),with a decreased trend and a net reduction rate of
0.15 Pg C yr^(-1).The areas that exhibited reductions were concentrated in South America,Central Africa,and Southeast Asia,and those with increments were scattered in Northwestern North America,Eastern South America,Central Africa,East Asia,and parts of Southeast Asia.For the indirect carbon emissions from the utilization of built-up land(indirect ELUC),it manifested an upward trend with a total emission of 27.51 Pg C(1.2 Pg C yr^(-1)).The total value resulted by global ELUC was $136.3×10^(9) US,and the value of annual was equivalent to 3.7 times the GDP of the Central African Republic in 2015($5.93×10^(9) US yr^(-1)).Among the 79 countries and regions considered in this study,54 represented the upward GDP with increased emissions,and only 25 experienced GDP growth with emission reductions.These findings highlight the pivotal role of land use change in the carbon cycle and the significance of coordinated development between GDP and carbon emissions.