scholarly journals Inoculation of paddy soils with Rhodopseudomonas palustris enhanced heavy metal immobilisation

2021 ◽  
Vol 67 (No. 1) ◽  
pp. 55-60
Author(s):  
Xian Xiao ◽  
Yan Zhu ◽  
Yuexiang Gao ◽  
Jing Fu ◽  
Yuan Zhao ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Bacillus Subtilis ◽  
Rhodopseudomonas Palustris ◽  
Paddy Soils ◽  
Optimal Dosage ◽  
Soil Heavy Metal ◽  
Rice Grains ◽  
Pot Experiments ◽  
Metal Contents

To investigate the effect of microbial inoculum on soil heavy metal immobilisation, pot experiments were conducted with paddy soils contaminated by cadmium (Cd), lead (Pb), arsenic (As), and mercury (Hg), respectively. The results showed that the inoculation of Rhodopseudomonas palustris was more effective in the immobilisation of Pb and Cd in soils than the composite of R. palustris and Bacillus subtilis. Interestingly, a lower dosage of inoculum immobilised significantly more heavy metals than the higher dosage, potentially due to the competition of bacteria with limited nutrients. The heavy metal contents in rice grains also supported this finding, as less Pb and Cd were accumulated under the lower dosage. However, there were limited effects of microbial inoculations on the immobilisation of Hg and As. In general, our study indicated the effectiveness of R. palustris in immobilising Pb and Cd in soils and highlighted the importance of determining the optimal dosage of inoculum in bioremediation.  

scholarly journals Integrating a Hybrid Back Propagation Neural Network and Particle Swarm Optimization for Estimating Soil Heavy Metal Contents Using Hyperspectral Data

2019 ◽  
Vol 11 (2) ◽  
pp. 419 ◽  
Author(s):  
Piao Liu ◽  
Zhenhua Liu ◽  
Yueming Hu ◽  
Zhou Shi ◽  
Yuchun Pan ◽  
...  
Keyword(s):  
Neural Network ◽  
Heavy Metals ◽  
Heavy Metal ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Hyperspectral Data ◽  
Estimation Accuracy ◽  
Soil Heavy Metals ◽  
Soil Heavy Metal ◽  
Metal Contents

Soil heavy metals affect human life and the environment, and thus, it is very necessary to monitor their contents. Substantial research has been conducted to estimate and map soil heavy metals in large areas using hyperspectral data and machine learning methods (such as neural network), however, lower estimation accuracy is often obtained. In order to improve the estimation accuracy, in this study, a back propagation neural network (BPNN) was combined with the particle swarm optimization (PSO), which led to an integrated PSO-BPNN method used to estimate the contents of soil heavy metals: Cd, Hg, and As. This study was conducted in Guangdong, China, based on the soil heavy metal contents and hyperspectral data collected from 90 soil samples. The prediction accuracies from BPNN and PSO-BPNN were compared using field observations. The results showed that, 1) the sample averages of Cd, Hg, and As were 0.174 mg/kg, 0.132 mg/kg, and 9.761 mg/kg, respectively, with the corresponding maximum values of 0.570 mg/kg, 0.310 mg/kg, and 68.600 mg/kg being higher than the environment baseline values; 2) the transformed and combined spectral variables had higher correlations with the contents of the soil heavy metals than the original spectral data; 3) PSO-BPNN significantly improved the estimation accuracy of the soil heavy metal contents, with the decrease in the mean relative error (MRE) and relative root mean square error (RRMSE) by 68% to 71%, and 64% to 67%, respectively. This indicated that the PSO-BPNN provided great potential to estimate the soil heavy metal contents; and 4) with the PSO-BPNN, the Cd content could also be mapped using HuanJing-1A Hyperspectral Imager (HSI) data with a RRMSE value of 36%, implying that the PSO-BPNN method could be utilized to map the heavy metal content in soil, using both field spectral data and hyperspectral imagery for the large area.

Analysis of the Change of Heavy Metal Contents in Farmland in Mengcheng

2012 ◽  
Vol 178-181 ◽  
pp. 773-776
Author(s):  
Guo Wei Xu ◽  
Xue Wu ◽  
Su Ling Huang ◽  
Xin Tian Yuan ◽  
Yang Gao ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Content ◽  
Heavy Metal Content ◽  
National Standard ◽  
Soil Heavy Metal ◽  
Metal Contents ◽  
Survey Results ◽  
Changing Rate

In order to find out the variations of soil heavy metal contents in Mengcheng, the heavy metal of the soil was tested in the same way in 2010, based on the survey results of 2001. The results showed that the contents of the 8 kinds of heavy metal in Mengcheng County were lower than those of the national standard, but the heavy metal content of Mengcheng County in 2010 were significantly higher than those in 2001, especially Pb, and the content of Hg, Ni, As also increased greatly; The increased of changing rate of various heavy metals contents are in the following descending order: Pb> Hg> Ni> As> Cu> Cd> Cr> Zn. The uneven dispersion of various heavy metals element in different sections of Mengcheng County also increased.

scholarly journals Heavy Metal Contents and Assessment of Soil Contamination in Different Land-Use Types in the Qaidam Basin

2021 ◽  
Vol 13 (21) ◽  
pp. 12020
Author(s):  
Bayan Nuralykyzy ◽  
Pan Wang ◽  
Xiaoqian Deng ◽  
Shaoshan An ◽  
Yimei Huang
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Land Use ◽  
Soil Contamination ◽  
Qaidam Basin ◽  
Rapid Development ◽  
Quality Standard ◽  
Soil Heavy Metal ◽  
Land Use Types ◽  
Metal Contents

Due to the unique geographical location and rapid development in the agricultural industry, heavy metals’ risk of soil contamination in the Qaidam Basin is gradually increasing. The following study was conducted to determine the soil heavy metal contents under different types of land use, contamination levels, and the physicochemical properties of soil. Soil samples were collected from facility lands, orchards, farmlands, and grasslands at 0–10 and 10–20 cm soil layers. Heavy metals including copper (Cu), chromium (Cr), nickel (Ni), zinc (Zn), lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg) were analyzed using inductively coupled plasma mass spectrometry and the soil was evaluated with different methods. Overall, the average Cu (25.07 mg/kg), Cr (45.67 mg/kg), Ni (25.56 mg/kg), Zn (71.24 mg/kg), Pb (14.19 mg/kg), Cd (0.17 mg/kg), As (12.54 mg/kg), and Hg (0.05 mg/kg) were lower than the environmental quality standard. However, the Cu, Cr, Ni, and As were highest in farmland, and Zn and Hg were highest in the facility land. The Pb content was highest in orchards, and the Cd content was the same in facility land, orchards, and farmland. Among the different land-use types, the soil heavy metal concentrations decreased in the order of facility land > farmland > grassland > orchards. The pH was alkaline, the content of SOC (soil organic carbon) 15.76 g/kg in grassland, TN (total nitrogen) 1.43 g/kg, and TP (total phosphorus) 0.97 g/kg in facility land showed the highest result. The soil BD (bulk density) had a significant positive correlation with Cu, Cr, Ni, Zn, Pb, Cd, and the TP positively correlated with Cu, Zn, Cd, and Hg. The soil evaluation results of the comprehensive pollution index indicated that the soil was in a clean condition. The index of potential environmental risk indicates that heavy metals are slightly harmful to the soil.

scholarly journals Heavy-Metal Contents and the Impact of Roasting on Polyphenols, Caffeine, and Acrylamide in Specialty Coffee Beans

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1310
Author(s):  
Matúš Várady ◽  
Sylwester Ślusarczyk ◽  
Jana Boržíkova ◽  
Katarína Hanková ◽  
Michaela Vieriková ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Dry Matter ◽  
Green Beans ◽  
Caffeoylquinic Acids ◽  
Coffee Beans ◽  
Metal Contents ◽  
Specialty Coffee ◽  
Quantitative Analyses ◽  
The Impact

The aim of this study was to determine the effect of roasting on the contents of polyphenols (PPH), acrylamide (AA), and caffeine (CAF) and to analyze heavy metals in specialty coffee beans from Colombia (COL) and Nicaragua (NIC). Samples of NIC were naturally processed and COL was fermented anaerobically. Green beans from COL (COL-GR) and NIC (NIC-GR) were roasted at two levels, light roasting (COL-LIGHT and NIC-LIGHT) and darker roasting (COL-DARK and NIC-DARK), at final temperatures of 210 °C (10 min) and 215 °C (12 min), respectively. Quantitative analyses of PPH identified caffeoylquinic acids (CQA), feruloylquinic acids, and dicaffeoylquinic acids. Isomer 5-CQA was present at the highest levels and reached 60.8 and 57.7% in COL-GR and NIC-GR, 23.4 and 29.3% in COL-LIGHT and NIC-LIGHT, and 18 and 24.2% in COL-DARK and NIC-DARK, respectively, of the total PPH. The total PPH contents were highest in COL-GR (59.76 mg/g dry matter, DM). Roasting affected the contents of PPH, CAF, and AA (p < 0.001, p < 0.011 and p < 0.001, respectively). Nickel and cadmium contents were significantly higher in the COL-GR than in the NIC-GR beans. Darker roasting decreased AA content, but light roasting maintained similar amounts of CAF and total PPH.

Assessing Soil and Plant Pollution by Abandoned Rural Waste Dumping Sites in Ningbo, China

2011 ◽  
Vol 138-139 ◽  
pp. 1149-1155 ◽  
Author(s):  
Yi Dong Guan ◽  
Ye Hong Du ◽  
Zhen Dong Li ◽  
An Cheng Luo
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Reference Value ◽  
Dry Weight ◽  
Rice Grain ◽  
Contamination Assessment ◽  
Plant Parts ◽  
Metal Contents ◽  
Plant Pollution

This paper reports the concentration of heavy metals (Cr, Cu, Zn, Cd and Pb) in the soils and rices surrounding the abandoned rural waste dumping sites in Ningbo. Igeo (geoaccumulation index) was calculated to assess the contamination degree of heavy metals in soils. The mean contents of Cr, Cu, Cd, Zn and Pb of soils were 33.3, 24.1, 1.5, 118.9 and 45.6 mg/(kg DW) (dry weight), respectively. All of them were much higher than that of the reference value (i.e. CK), but there were no coherent trend of the metal contents within 1-120m distance from the dumping site. Igeo of heavy metals reveals the order of Cd>Cu>Cr>Pb>Zn, and the contamination assessment of soils using Igeo indicate the moderate Cd pollution, while the soils were unpolluted-moderately overall by Cr, Cu, Zn as well as Pb. The heavy metal contents in root, stem & leaf and rice grains were all remarkable higher than that of the CK at 20-120 m distances, and the heavy metal contents in root were evidently much higher than other plant parts, while those in rice grain were lowest, indicating the great bioaccumulation trend of heavy metals. Although the metal contents in the rice grain were within the legislation limit, its bioaccumulation trend of heavy metals was remarkable, whose contents were 4.38-fold for Cr, 1.76-fold for Cu, 1.28-fold for Zn, 2.67-fold for Cd and 3.03-fold for Pb higher than that of reference value, respectively. Finally, we proposed a decentralized in-situ restoration approach for the dumping sites.

scholarly journals Spatial Connections between Microplastics and Heavy Metal Pollution within Floodplain Soils

2022 ◽  
Vol 12 (2) ◽  
pp. 595
Author(s):  
Collin J. Weber ◽  
Jens Hahn ◽  
Christian Opp
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Wide Distribution ◽  
Soil Material ◽  
Statistical Correlations ◽  
Floodplain Soils ◽  
Icp Ms ◽  
Metal Contents ◽  
Sediment Layers ◽  
Deposition Conditions

Soils contain an increasing number of different pollutants, which are often released into the environment by human activity. Among the “new” potential pollutants are plastics and microplastics. “Recognized” pollutants such as heavy metals, of geogenic and anthropogenic origin, now meet purely anthropogenic contaminants such as plastic particles. Those can meet especially in floodplain landscapes and floodplain soils, because of their function as a temporary sink for sediments, nutrients, and pollutants. Based on a geospatial sampling approach, we analyzed the soil properties and heavy metal contents (ICP-MS) in soil material and macroplastic particles, and calculated total plastic concentrations (Ptot) from preliminary studies. Those data were used to investigate spatial connections between both groups of pollutants. Our results from the example of the Lahn river catchment show a low-to-moderate contamination of the floodplain soils with heavy metals and a wide distribution of plastic contents up to a depth of two meters. Furthermore, we were able to document heavy metal contents in macroplastic particles. Spatial and statistical correlations between both pollutants were found. Those correlations are mainly expressed by a comparable variability in concentrations across the catchment and in a common accumulation in topsoil and upper soil or sediment layers (0–50 cm). The results indicate comparable deposition conditions of both pollutants in the floodplain system.

scholarly journals Erkenez Çayı’nda (Kahramanmaraş) Süt Ürünleri, Boya ve Tekstil Fabrikası Atık Sularından Kaynaklanan Ağır Metal Kirliliğinin Belirlenmesi

2019 ◽  
Vol 7 (11) ◽  
pp. 1858
Author(s):  
Özgür Canpolat ◽  
Ece Vanlı
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Quality Criteria ◽  
Water Quality Criteria ◽  
Milk Products ◽  
Metal Contents ◽  
Considerable Impact ◽  
Textile Factory

Industries, as a source of pollution, have a considerable impact on aquatic ecosystems due to the diversity in the composition of their wastewater. In this study, it is aimed to determine the heavy metal pollution caused by the wastewater of milk products factory, paint factory and textile factory in the Organized Industrial Zone of Kahramanmaraş province. For this purpose, seasonal concentrations of some heavy metals (Fe, Cu, Zn, Cr, Ni, Cd, As and Hg) have been determined in wastewaters of milk products factory, paint factory and textile factory and in the region where these wastewaters discharge in the Erkenez Stream. The seasonal variation of heavy metals in all stations, generally the lowest concentrations of all elements were determined in winter and the highest concentrations were determined in summer. When the heavy metal contents of milk products factory, paint factory and textile factory wastewaters were compared, the highest values were found in textile factory wastewater. When all stations are taken into consideration, according to USEPA and water quality criteria, it is determined that the wastewaters of milk products factory, paint factory and textile factory and the area of the Erkenez Stream, where these wastewaters are discharged, were very dirty in term of heavy metals. When these results are taken into consideration, it is clear that the wastewater of these factories causes serious heavy metal pollution in the Erkenez Stream.

scholarly journals Heavy metals in the organic soil layer of beech forests in Serbia

2005 ◽  
pp. 55-67 ◽  
Author(s):  
Ratko Kadovic ◽  
Olivera Kosanin ◽  
Snezana Belanovic ◽  
Milan Knezevic
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Soil Layer ◽  
Forest Litter ◽  
Organic Soil ◽  
Organic Horizon ◽  
Beech Forests ◽  
Metal Contents ◽  
Level I ◽  
And Migration

During the last decades, forest ecosystems have been strongly exposed to the effect of different harmful pollutants, especially from the atmosphere. Harmful substances from the air, in addition to the direct effect on forest trees, also deposit in the soil, and have an adverse effect on soil chemistry and pedogenetic processes. The results of previous studies in Serbia (Kadovic, Knezevic, 2002, 2004) show some specificities regarding the accumulation and migration of heavy metals in the soil. The highest concentrations were found in the layers of forest litter and in the surface organo-mineral horizons. This paper presents the results of the study of heavy metal contents (Zn, Mn, Cu, Fe, Cd, Pb, Ni and Cr) in the organic horizon (forest litter) of beech forests in Serbia. The study of the heavy metal content in the organic horizon (forest litter) is very significant primarily in the aim of monitoring the trend of their migration through the soil profile and the effect on the soil properties and genesis. The soil quality in beech forests in Serbia was assessed within the Project ICP Forest, Level I, by the methodology UN/ECE-EC, 2000.

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