scholarly journals Characteristics and Influencing Factors of Microbial Community in Heavy Metal Contaminated Soil under Silicon Fertilizer and Biochar Remediation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jiachao Zhang ◽  
Yuewei He ◽  
Yingchun Fang ◽  
Keqi Zhao ◽  
Nanyi Wang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Microbial Community ◽  
Quantitative Pcr ◽  
Phospholipid Fatty Acid ◽  
Principal Component ◽  
Metal Availability ◽  
Nitrogen And Phosphorus ◽  
Soil Microbial Community Structure ◽  
Silicon Fertilizer

Silicon fertilizer and biochar have been widely used to remediate soil contaminated by heavy metals. The effects and mechanism of silicon fertilizer and biochar addition on the heavy metal availability, soil biological properties, and microbial community characteristics need further study in soils contaminated by heavy metals. Therefore, this research determined how silicon fertilizer, biochar, and their combined using affected microbial communities related with nitrogen and phosphorus cycling. The abundance and composition of the microbial community were evaluated by quantitative PCR and phospholipid fatty acid analysis, respectively. Results showed that silicon fertilizer and biochar addition significantly changed soil properties, including pH, total organic carbon, ammonium, nitrate. The Cd and Zn speciation were significantly reduced by silicon fertilizer, biochar, and their integrated application. Microbial community abundance and structure were also significantly changed. Principal component analysis shows that the difference in soil microbial community structure is the most obvious under the combined addition of biochar, silicon fertilizer and biochar. In addition, the results of fluorescence quantitative PCR showed that with biological addition, the number of soil bacteria was significantly reduced. This study reveals the influence of silicon fertilizer and biochar on bacterial and fungal communities in heavy metal soils and the effect of soil heavy metal availability.

Risk estimation and multivariate statistical analysis of the heavy metal content of drinking water samples

2018 ◽  
Vol 34 (10) ◽  
pp. 714-725
Author(s):  
Rajan Jakhu ◽  
Rohit Mehra
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Drinking Water ◽  
Statistical Analysis ◽  
Water Samples ◽  
Multivariate Statistical Analysis ◽  
Inductively Coupled Plasma ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Drinking Water Samples

Drinking water samples of Jaipur and Ajmer districts of Rajasthan, India, were collected and analyzed for the measurement of concentration of heavy metals. The purpose of this study was to determine the sources of the heavy metals in the drinking water. Inductively coupled plasma mass spectrometry was used for the determination of the heavy metal concentrations, and for the statistical analysis of the data, principal component analysis and cluster analysis were performed. It was observed from the results that with respect to WHO guidelines, the water samples of some locations exceeded the contamination levels for lead (Pb), selenium (Se), and mercury (Hg), and with reference to the EPA guidelines, the samples were determined unsuitable for drinking because of high concentrations of Pb and Hg. Using multivariate statistical analysis, we determined that copper, manganese, arsenic, Se, and Hg were of anthropogenic origin, while Pb, copper, and cadmium were of geogenic origin. The present study reports the dominance of the anthropogenic contributions over geogenics in the studied area. The sources of the anthropogenic contaminants need to be investigated in a future study.

Multivariate analyses on heavy metal binding fractions of river sediments in Southern Taiwan

2000 ◽  
Vol 42 (7-8) ◽  
pp. 193-199 ◽  
Author(s):  
K. C. Yu ◽  
C. Y. Chang ◽  
L. J. Tsai ◽  
S. T. Ho
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Organic Matter ◽  
Metal Binding ◽  
River Sediments ◽  
Principal Component ◽  
Fe Oxides ◽  
Data Points ◽  
Southern Taiwan ◽  
Highly Correlated

This study depicts the amounts of heavy metals (Cu, Zn, Pb, Cr, Co, and Ni) bound to four geochemical compositions of sediments (carbonates, Mn oxides, Fe oxides, and organic matters), and the correlations between various geochemical compositions and their heavy-metal complexes. Hundreds of data, obtained from sediments of five main rivers (located in southern Taiwan), were analyzed by using multivariate analysis method. Among the four different geochemical compositions, the total amount of the six heavy metals bound to organic matter is the highest. Zn is easily bound to various geochemical compositions, especially carbonates in sediments of the Yenshui river and the Potzu river (i.e., the heavily heavy-metal polluted sediments); Cr, Pb, and Ni are mainly bound to both Fe oxides and organic matter; Cu has high affinity to organic matter. By performing principal component analyses, the data points of organic matter and both Pb and Cu associated with organic matter cluster together in sediments ofthe Peikang, the Potzu, and the Yenshui rivers, which indicates both Pb and Cu might be discharged from the same pollution sources in these rivers. Moreover, correlations between any two binding fractions of heavy metal associated with Fe oxides in different rivers are not consistent, which indicates some factors including the binding sites of Fe oxides, the extent of heavy metal pollution, binding competitions between heavy metals may affect the amounts of heavy metals bound to Fe oxides. Furthermore, it should be noted that the amount of Pb bound to Fe oxides is highly correlated with the amount of Fe oxides in sediments of the Peikang, the Potzu, and the Yenshui rivers.

Impact of Humics and Plants on Microbial Community and Petroleum Hydrocarbon Degradation in Contaminated Soil

2013 ◽  
Vol 726-731 ◽  
pp. 131-140
Author(s):  
Hai Hua Jiao ◽  
Kai Wang ◽  
Jian Gang Pan ◽  
De Cai Jin ◽  
Zhan Bin Huang ◽  
...  
Keyword(s):  
Microbial Community ◽  
Soil Microbial Community ◽  
Petroleum Hydrocarbon ◽  
Phospholipid Fatty Acid ◽  
Principal Component ◽  
Total Petroleum Hydrocarbon ◽  
Crop Species ◽  
Functional Activities ◽  
Soil Microbial ◽  
Gram Positive Bacteria

A greenhouse pot experiment, in which 3 different crops (wheat, cabbage, spinach) were cultivated in soil with and without humics (HS), was conducted to evaluate the effect of HS on soil microbiological properties. Phospholipid fatty acid (PLFA) profiles were analyzed to reveal the microbial community structure. As a measure of the functional activity of soil microbial community, the ratio of degraded to total petroleum hydrocarbon in soil was estimated. The results indicated that HS had an important effect on the soil microbial community and its functional activities. First, the principal component analysis (PCA) of the PLFA signatures revealed marked changes between soil with HS and without HS. In addition, the total amount and the profile of PLFA were significantly different between the untreated and HS-amended soils. Using PLFA patterns as a biomarker, it was found that gram-positive bacteria (G+) were more sensitive to HS than gram-negative bacteria (G-), and the biomass of G+ was higher in soil with HS than in that without HS. Second, the crop could stimulate the growth of soil microorganisms; however, the differences depended clearly on the crop species. The G+ and G- biomass was increased in spinach soil containing HS, but was decreased in wheat and cabbage soils. The population of fungi was increased in wheat and spinach soils containing HS, but was decreased in cabbage soil. The population of actinomycetes was increased in cabbage soil, but was decreased in wheat and spinach soils containing HS. Third, the ratio of degraded to total petroleum hydrocarbon was also affected by the HS treatment. It was slightly increased in soil with HS treatment, but a significant change depended on the crop species. In general, fatty acids ranged from C13 to C19. In total, 25 different PLFAs were identified, including saturated (SAT), monounsaturated (MUFA), branched (BR), and polyunsaturated (PUFA) species. There was a clear difference in the PLFA composition between soils with and without HS.

scholarly journals Soil Microbial Community Structure and Target Organisms under Different Fumigation Treatments

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Sadikshya R. Dangi ◽  
James S. Gerik ◽  
Rebecca Tirado-Corbalá ◽  
Husein Ajwa
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Microbial Community Structure ◽  
Methyl Bromide ◽  
Soil Microorganisms ◽  
Phospholipid Fatty Acid ◽  
Natural Soil ◽  
Soil Microbial Community Structure ◽  
Soil Microbial ◽  
Field Samples

Producers of several high-value crops in California rely heavily on soil fumigants to control key diseases, nematodes, and weeds. Fumigants with broad biocidal activity can affect both target and nontarget soil microorganisms. The ability of nontarget soil microorganisms to recover after fumigation treatment is critical because they play an important role in sustaining the health of agricultural and natural soil systems. Fumigation trial was conducted in Parlier, CA, and the study focuses on the effects of different rates of Telone C35 and also methyl bromide fumigation with polyethylene (PE) and totally impermeable film (TIF) tarps on target and nontarget soil microorganisms using field samples. Results indicated that the populations of target organisms, such asFusarium oxysporumandPythiumspp., were reduced at all rates of fumigants. Phospholipid fatty acid (PLFA) analysis indicated that all major nontarget soil microbial groups such as Gram positive bacteria, Gram negative bacteria, fungi, and arbuscular mycorrhizal fungi (AMF) were affected by methyl bromide (MeBr) fumigation treatment. In general, the effects of Telone C35 (299 L/ha) under PE tarp had the least impact on microbial community structure and better effect on controlling target microorganisms and, therefore, indicated the better option among fumigation treatments.

Investigation of Soil Heavy Metal in Zhehai Town Huize County Yunnan Based on GIS- Approach and Geostatistics

2012 ◽  
Vol 610-613 ◽  
pp. 3067-3074
Author(s):  
Kun Shi ◽  
Dong Sheng Li ◽  
Bi Yun Zhao
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Correlation Matrix ◽  
Yunnan Province ◽  
Anthropogenic Activities ◽  
Principal Component ◽  
And Cluster Analysis ◽  
Soil Area

1144 sample points were collected using PXRF from an area of 99 square kilometers soil area Zhehai town Huizhe county of Yunnan province to acquire their concentrations and possible sources, and characterize their spatial variability for risk assessment. SPSS16.0 was used to deal the raw date and eliminate the outfits and perform Multivariate analysis (correlation matrix, principal component analysis, and cluster analysis). It discriminate distinct groups of heavy metals. From the Range of the semi-variorum models, it obtained elements spatial structure and the contamination resource caused mainly by natural resource or anthropogenic activities. The result of risk assessment attained the percentage of pollution accounts for whole investigate region, which provides the reference to deal with the soil pollution.

Soil Microbial Community Structure in Tree Peony (Paeonia suffruticosa) Garden Based on PLFA Analysis

2014 ◽  
Vol 675-677 ◽  
pp. 82-85
Author(s):  
Dong Xue ◽  
Xiang Dong Huang ◽  
Lian Xue
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Microbial Community Structure ◽  
Soil Microbial Community ◽  
Phospholipid Fatty Acid ◽  
Shannon Index ◽  
Tree Peony ◽  
Soil Microbial Community Structure ◽  
Soil Microbial ◽  
Chronological Change

Understanding the chronological change in soil microbial community structure of tree peony garden ecosystem is important from ecological, environmental, and management perspectives. Soil samples were collected from three tree peony garden systems (5-, 12-, and 25-year-old tree peony gardens), and adjacent wasteland at Luoyang, Henan Province of China. Soil microbial community structure was analyzed by phospholipid fatty acid (PLFA) method. The bacterial and actinomycete PLFAs increased from the wasteland to 5-year-old tree peony garden and then decreased from the 5- to 25-year-old tree peony garden, and the fungal PLFA first increased and then decreased with the increasing planting years, with the greatest amount found in the 12-year-old tree peony garden. The conversion from the wasteland to tree peony garden resulted in a significant increase in Shannon index, Richness, and Evenness. However, with the succeeding development of tree peony garden ecosystems, Shannon index, Richness, and Evenness decreased from the 5- to 25-year-old tree peony garden.

scholarly journals Genotypic and Phenotypic Responses of a Riverine Microbial Community to Polycyclic Aromatic Hydrocarbon Contamination

1998 ◽  
Vol 64 (9) ◽  
pp. 3422-3428 ◽  
Author(s):  
Donald E. Langworthy ◽  
Raymond D. Stapleton ◽  
Gary S. Sayler ◽  
Robert H. Findlay
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Nucleic Acid ◽  
Microbial Community Structure ◽  
Phospholipid Fatty Acid ◽  
Principal Component ◽  
Dry Weight ◽  
Hydrocarbon Contamination ◽  
Polycyclic Aromatic ◽  
Nucleic Acid Analysis

ABSTRACT The phenotypic and genotypic adaptation of a freshwater sedimentary microbial community to elevated (22 to 217 μg g [dry weight] of sediment−1) levels of polycyclic aromatic hydrocarbons (PAHs) was determined by using an integrated biomolecular approach. Central to the approach was the use of phospholipid fatty acid (PLFA) profiles to characterize the microbial community structure and nucleic acid analysis to quantify the frequency of degradative genes. The study site was the Little Scioto River, a highly impacted, channelized riverine system located in central Ohio. This study site is a unique lotic system, with all sampling stations having similar flow and sediment characteristics both upstream and downstream from the source of contamination. These characteristics allowed for the specific analysis of PAH impact on the microbial community. PAH concentrations in impacted sediments ranged from 22 to 217 μg g (dry weight) of sediment−1, while PAH concentrations in ambient sediments ranged from below detection levels to 1.5 μg g (dry weight) of sediment−1. Total microbial biomass measured by phospholipid phosphate (PLP) analysis ranged from 95 to 345 nmol of PLP g (dry weight) of sediment−1. Nucleic acid analysis showed the presence of PAH-degradative genes at all sites, although observed frequencies were typically higher at contaminated sites. Principal component analysis of PLFA profiles indicated that moderate to high PAH concentrations altered microbial community structure and that seasonal changes were comparable in magnitude to the effects of PAH pollution. These data indicate that this community responded to PAH contamination at both the phenotypic and the genotypic level.

scholarly journals Analysis and Source Identification of Heavy Metals in Soils of Central Urban Area of Chongqing, China

2021 ◽  
Author(s):  
Wende Chen ◽  
Kun Zhu ◽  
Yankun Cai ◽  
Peihao Peng
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Hot Spot ◽  
Central City ◽  
Principal Component ◽  
Parent Material ◽  
Soil Heavy Metal ◽  
Component Loading

Abstract In megacities, due to frequent human activities, large amounts of metals enter the soil indirectly or directly and eventually flow to people through the food chain. Therefore, the analysis and identification of soil heavy metal sources is an important part of revealing soil heavy metal pollution. The spatial content and potential sources of 11 heavy metals were analyzed from 342 surface soil samples collected from the central city of Chongqing in southwest China. The results showed that the main heavy metal elements under the first principal component loading were copper (Cu), nickel(Ni), zinc (Zn), manganese (Mn), cadmium (Cr), plumbum (Pb) and cadmium (Cd). The second principal component (F2) was mainly loaded with molybdenum (Mo), arsenic (As), mercury (Hg) and antimony (Sb), and the PCA-APCs receptor model of 11 heavy metals was constructed. The PCA-APCs receptor models of 11 heavy metals were constructed. The results of classification regression analysis confirmed the main sources of heavy metals. Population density mainly affected Cu (0.539), soil mainly affected Ni (0.411), Sb (0.493), Zn (0.472) and Mn (0.206), and water quality mainly affected As (0.453) and Mo (0.374). Air quality mainly affects Cd (0.332) and Cr (0.371), traffic activity mainly affects Hg (0.312), and slope mainly affects Pb (0.313). Hot spot analysis showed that heavy metals had a high degree of coincidence with environmental factors such as soil parent material, slope, soil type and traffic activities. The results of this study can be effectively used to make scientific decisions and strategies, and an effective strategy for prevention and control of soil heavy metal pollution should be formulated to protect the urban soil environmental quality.

scholarly journals Assessment of Soil Microbial Community Structure by Use of Taxon-Specific Quantitative PCR Assays

2005 ◽  
Vol 71 (7) ◽  
pp. 4117-4120 ◽  
Author(s):  
Noah Fierer ◽  
Jason A. Jackson ◽  
Rytas Vilgalys ◽  
Robert B. Jackson
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Quantitative Pcr ◽  
Microbial Community Structure ◽  
Soil Microbial Community ◽  
Soil Microbial Community Structure ◽  
Soil Microbial ◽  
Pcr Assays ◽  
Bacteria And Fungi ◽  
Taxonomic Groups

ABSTRACT Here we describe a quantitative PCR-based approach to estimating the relative abundances of major taxonomic groups of bacteria and fungi in soil. Primers were thoroughly tested for specificity, and the method was applied to three distinct soils. The technique provides a rapid and robust index of microbial community structure.

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