scholarly journals Inversion of Soil Heavy Metal Content Based on Spectral Characteristics of Peach Trees

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1208
Author(s):  
Wei Liu ◽  
Qiang Yu ◽  
Teng Niu ◽  
Linzhe Yang ◽  
Hongjun Liu
Keyword(s):  
Heavy Metal ◽  
Multiple Regression ◽  
Metal Content ◽  
Heavy Metal Contamination ◽  
Agricultural Soils ◽  
Spectral Characteristics ◽  
Hyperspectral Data ◽  
Heavy Metal Content ◽  
Soil Heavy Metal ◽  
Metal Monitoring

There exists serious heavy metal contamination of agricultural soils in China. It is not only time- and labor-intensive to monitor soil contamination, but it also has limited scope when using conventional chemical methods. However, the method of the heavy metal monitoring of soil based on vegetation hyperspectral technology can break through the vegetation barrier and obtain the heavy metal content quickly over large areas. This paper discusses a highly accurate method for predicting the soil heavy metal content using hyperspectral techniques. We collected leaf hyperspectral data outdoors, and also collected soil samples to obtain heavy metal content data using chemical analysis. The prediction model for heavy metal content was developed using a difference spectral index, which was not highly satisfactory. Subsequently, the five factors that have a strong influence on the content of heavy metals were analyzed to determine multiple regression models for the elements As, Pb, and Cd. The results showed that the multiple regression model could better estimate the heavy metal content with stable fitting that has high prediction accuracy compared with the linear model. The results of this research provide a scientific basis and technical support for the hyperspectral inversion of the soil heavy metal content.

scholarly journals Estimation of Soil Heavy Metal Content Using Hyperspectral Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1464 ◽  
Author(s):  
Zhenhua Liu ◽  
Ying Lu ◽  
Yiping Peng ◽  
Li Zhao ◽  
Guangxing Wang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Content ◽  
Regional Scale ◽  
Soil Samples ◽  
Hyperspectral Data ◽  
Heavy Metal Content ◽  
Soil Heavy Metal ◽  
Relationship Of ◽  
The Relationship

Quickly and efficiently monitoring soil heavy metal content is crucial for protecting the natural environment and for human health. Estimating heavy metal content in soils using hyperspectral data is a cost-efficient method but challenging due to the effects of complex landscapes and soil properties. One of the challenges is how to make a lab-derived model based on soil samples applicable to mapping the contents of heavy metals in soil using air-borne or space-borne hyperspectral imagery at a regional scale. For this purpose, our study proposed a novel method using hyperspectral data from soil samples and the HuanJing-1A (HJ-1A) HyperSpectral Imager (HSI). In this method, estimation models were first developed using optimal relevant spectral variables from dry soil spectral reflectance (DSSR) data and field observations of soil heavy metal content. The relationship of the ratio of DSSR to moisture soil spectral reflectance (MSSR) with soil moisture content was then derived, which built up the linkage of DSSR with MSSR and provided the potential of applying the models developed in the laboratory to map soil heavy metal content at a regional scale using hyperspectral imagery. The optimal relevant spectral variables were obtained by combining the Boruta algorithm with a stepwise regression and variance inflation factor. This method was developed, validated, and applied to estimate the content of heavy metals in soil (As, Cd, and Hg) in Guangdong, China, and the Conghua district of Guangzhou city. The results showed that based on the validation datasets, the content of Cd could be reliably estimated and mapped by the proposed method, with relative root mean square error (RMSE) values of 17.41% for the point measurements of soil samples from Guangdong province and 17.10% for the Conghua district at the regional scale, while the content of heavy metals As and Hg in soil were relatively difficult to predict with the relative RMSE values of 32.27% and 28.72% at the soil sample level and 51.55% and 36.34% at the regional scale. Moreover, the relationship of the DSSR/MSSR ratio with soil moisture content varied greatly before the wavelength of 1029 nm and became stable after that, which linked DSSR with MSSR and provided the possibility of applying the DSSR-based models to map the soil heavy metal content at the regional scale using the HJ-1A images. In addition, it was found that overall there were only a few soil samples with the content of heavy metals exceeding the health standards in Guangdong province, while in Conghua the seriously polluted areas were mainly distributed in the cities and croplands. This study implies that the new approach provides the potential to map the content of heavy metals in soil, but the estimation model of Cd was more accurate than those of As and Hg.

Heavy Metal Content of Agricultural Soils at Tumu, Akko Local Government Area of Gombe State, Nigeria

2019 ◽  
Vol 9 (2) ◽  
pp. p8693
Author(s):  
Ogidi A. Ogidi ◽  
Danja B. A. ◽  
Sanusi K. A. ◽  
Nathaniel Sunday Samuel ◽  
Abdurrahman Abubakar ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Local Government ◽  
Metal Content ◽  
Agricultural Soils ◽  
Local Government Area ◽  
Heavy Metal Content

Soil heavy metal content on the hillslope region of Rio de Janeiro, Brazil: reference values

2018 ◽  
Vol 190 (6) ◽  
Author(s):  
Erica Souto Abreu Lima ◽  
Talita de Santana Matos ◽  
Helena Saraiva Koenow Pinheiro ◽  
Leonardo Durval Duarte Guimarães ◽  
Daniel Vidal Pérez ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Reference Values ◽  
Rio De Janeiro ◽  
Metal Content ◽  
Heavy Metal Content ◽  
Soil Heavy Metal

scholarly journals Analisis Kandungan Logam Berat Pada Ikan Kakap Putih (Lates calcarifer Bloch) di Perairan Mimika Papua

2019 ◽  
Vol 17 (2) ◽  
pp. 256
Author(s):  
Rosye H.R. Tanjung ◽  
Suwito Suwito ◽  
Vita Purnamasari ◽  
Suharno Suharno
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Content ◽  
Heavy Metal Contamination ◽  
Sea Water ◽  
Good Condition ◽  
Quality Standard ◽  
Heavy Metal Content ◽  
Lates Calcarifer ◽  
Tailings Sand

Kebutuhan bahan pangan sangat tergantung pada ketersediaanya di lingungan. Bahan pangan yang diperlukan untuk memenuhi kebutuhan sehari-hari harus sehat dan bebas dari bahan pencemar, termasuk logam berat. Ikan kakap putih (Lates calcarifer) sering dijumpai pada kawasan muara sungai di hampir seluruh wilayah Indonesia, bahkan di Papua. Tujuan penelitian ini adalah untuk mengkaji kandungan logam berat Pb, Cd, Cu, Fe, As, dan Hg pada ikan kakap putih (L. calcarifer) yang hidup di perairan estuari Mimika Papua. Perairan estuari di Mimika diketahui sebagai salah satu daerah pengendapan pasir sisa tambang (tailing). Metode yang digunakan adalah survei dan analisis laboratorium kandungan logam berat pada tubuh ikan. Analisis Pb, Cd, Cu, Fe, As, dan Hg ditentukan dengan spektroskopi serapan atom (AAS, Atomic Absorpsion Spectroscopy). Penentuan tingkat pencemaran logam berat dilakukan dengan Metode Standar APHA 3113 Cetac Technologies SPR IDA. Analisis data dilakukan dengan membandingkan kandungan logam berat dalam air dengan baku mutu air laut menurut SK MNLH No. 51 tahun 2004. Untuk kandungan logam berat pada organ tubuh ikan dibandingkan dengan kandungan maksimum logam berat berdasarkan SNI 7387: 2009 tentang batas maksimum cemaran logam berat bahan pangan. Kandungan logam berat pada ikan kakap putih masih tergolong aman dikonsumsi karena mengandung logam berat di bawah ambang batas baku mutu. Kondisi ini didukung oleh hasil analisis logam berat pada air yang menunjukkan masih dalam kondisi baik.   Kata kunci: L. calcarifer, logam berat, Sungai Kamora, Sungai Ajkwa, Mimika.   The need for food depends on the availability in the environment. Foods needed to meet daily needs should be healthy and free of pollutants, including heavy metals. White snapper (Lates calcarifer) is often found in the estuary of the river in almost all parts of Indonesia, even in Papua. The purpose of this research is to study the heavy metal content of Pb, Cd, Cu, Fe, As, and Hg on white snapper (L. calcarifer) which live in Mimika Papua estuary waters. The estuary waters of Mimika are known as one of the deposition areas of tailings sand. The method used is survey and laboratory analysis of heavy metal content in fish body. Analysis of Pb, Cd, Cu, Fe, and Hg was determined by Atomic Absorption Spectroscopy (AAS). Determination of the level of heavy metal contamination was done by Standard Method of APHA 3113 Cetac Technologies SPR IDA. Data analysis was done by comparing the heavy metal content in water with sea water quality standard according to SK MNLH No. 51 year 2004. For heavy metal content in fish body organs compared with maximum content of heavy metals based on SNI 7387: 2009 on the maximum limit of heavy metal food contamination. The content of heavy metals in white snapper is still considered safe for consumption because its below the quality standard threshold. This condition is supported by the results of heavy metal analysis on the water which shows still in good condition. Key words: L. calcarifer, heavy metal, Kamora River, Ajkwa River, Mimika.

Heavy Metal Contamination of Soil in Zhuzhou Smelting

2014 ◽  
Vol 926-930 ◽  
pp. 4246-4249
Author(s):  
Jing Yi Wang ◽  
Jiang Xue Long ◽  
Hong Wei Lu
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Zinc Sulfide ◽  
Metal Content ◽  
Heavy Metal Contamination ◽  
Microwave Digestion ◽  
Heavy Metal Content ◽  
Soil Survey ◽  
Deep Soil ◽  
Production Areas

To date, environmental issues become increasingly prominent, especially heavy metal (Pb and Zn) pollution of soil. This paper describes the procedure of detecting heavy metal content in soil from Zhuzhou Smelting in order to understand the contamination degree of heavy metals. An extensive soil survey was conducted in the plant include lead and zinc major production areas. Microwave digestion and ICP-AES technology were used to test metal content in soil. The results revealed that the soil in the area had been polluted by Pb and Zn, however, the pollution degree of each type of metals was not identical. In general, the Smelting was slightly polluted by heavy metals, with the highest concentration being in the Zinc sulfide plant. The heavy metal content in deep soil was a little bit higher than surface except for the Zinc sulfide plant. The reason may related to its particular location.

scholarly journals Chemometric approach to evaluate heavy metals’ content in Daucus Carota from different localities in Serbia

2015 ◽  
Vol 69 (6) ◽  
pp. 643-650 ◽  
Author(s):  
Violeta Mitic ◽  
Vesna Stankov-Jovanovic ◽  
Snezana Tosic ◽  
Aleksandra Pavlovic ◽  
Jelena Cvetkovic ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Principal Components ◽  
Daucus Carota ◽  
Metal Content ◽  
Heavy Metal Contamination ◽  
Principal Component ◽  
Heavy Metal Content ◽  
Chemometric Methods ◽  
Chemometric Approach ◽  
Components Analysis

The aim of this study was to evaluate heavy metal content in carrots (Daucus carota) from the different localities in Serbia and assess by the cluster analysis (CA) and principal components analysis (PCA) the heavy metal contamination of carrots from these areas. Carrot was collected at 13 locations in five districts. Chemometric methods (CA and PCA) were applied to classify localities according to heavy metal content in carrots. CA separated localities into two statistical significant clusters. PCA permitted the reduction of 12 variables to four principal components explaining 79.94% of the total variance. The first most important principal component was strongly associated with the value of Cu, Sb, Pb and Tl. This study revealed that CA and PCA appear useful tools for differentiation of localities in different districts using the profile of heavy metal in carrot samples.

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