scholarly journals Active biomonitoring of heavy metal pollution level of Wulihu area, Lake Taihu using "standardized" Anodonta woodiana

2014 ◽  
Vol 26 (6) ◽  
pp. 857-863 ◽  
Author(s):  
CHEN Xiubao ◽  
◽  
SU Yanping ◽  
LIU Hongbo ◽  
YANG Jian
Keyword(s):  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Lake Taihu ◽  
Pollution Level ◽  
Active Biomonitoring ◽  
Anodonta Woodiana

scholarly journals Analysis of the Impact of Rural Households’ Behaviors on Heavy Metal Pollution of Arable Soil: Taking Lankao County as an Example

2018 ◽  
Vol 10 (12) ◽  
pp. 4368 ◽  
Author(s):  
Shixin Ren ◽  
Erling Li ◽  
Qingqing Deng ◽  
Haishan He ◽  
Sijie Li
Keyword(s):  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Metal Content ◽  
Rural Households ◽  
Pollution Index ◽  
Arable Soil ◽  
Heavy Metal Content ◽  
Pollution Level ◽  
Single Factor

As heavy metal pollution of arable soil is a significant issue concerning the quality of agricultural products and human health, the rural households’ behaviors have a direct impact on heavy metal content in arable soil and its pollution level, but only a few researches have been done at such microscopic scale. Based on 101 field questionnaires of rural households in Lankao County and the monitoring data on heavy metal of arable soil of each rural household, the kind of rural households’ behaviors which impose obvious influence on heavy metal content of arable soil are investigated via single-factor pollution index, Nemerow pollution index and econometric model in this study. The results show that, rural households’ land utilization mode affects heavy metal content in soil, e.g., the degree of heavy metal pollution of soil for intensive planting is higher than that of traditional planting, viz. vegetable greenhouse > garlic land > traditional crop farmland. The management of cultivated land with due scale is beneficial to reducing heavy metal content in soil, that is, the land fragmentation degree is in direct proportion to heavy metal content in soil, so rural households are encouraged to carry out land circulation and combine the patch into a large one. Excess application of fertilizer, pesticide and organic fertilizer will lead to heavy metal pollution of soil, while agricultural technical training organized by government department and the foundation of agricultural cooperative can promote the technical level and degree of organization of rural households and enable them to be more scientific and rational in agrochemicals selection and application, hence reducing or avoiding heavy metal pollution of soil. Single factor pollution level of heavy metal in the soil for planting various crops is different, so it is recommended to prepare various pollution reduction programs for different land types and pollution levels for the harmony and unity of human-nature system.

scholarly journals Assessment of the Ecological Risk from Heavy Metals in the Surface Sediment of River Surma, Bangladesh: Coupled Approach of Monte Carlo Simulation and Multi-Component Statistical Analysis

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 180
Author(s):  
Arup Acharjee ◽  
Zia Ahmed ◽  
Pankaj Kumar ◽  
Rafiul Alam ◽  
M. Safiur Rahman ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ecological Risk ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
River Sediment ◽  
Risk Index ◽  
Pollution Level

River sediment can be used to measure the pollution level in natural water, as it serves as one of the vital environmental indicators. This study aims to assess heavy metal pollution namely Copper (Cu), Iron (Fe), Manganese (Mn), Zinc (Zn), Nickel (Ni), Lead (Pb), and Cadmium (Cd) in Surma River. Further, it compares potential ecological risk index values using Hakanson Risk Index (RI) and Monte Carlo Simulation (MCS) approach to evaluate the environmental risks caused by these heavy metals. in the study area. With obtained results, enrichment of individual heavy metals in the study area was found in the order of Ni > Pb > Cd > Mn > Cu > Zn. Also, variance in MCS index contributed by studied metals was in the order of Cd > Pb > Ni > Zn > Cu. None of the heavy metals, except Ni, showed moderate contamination of the sediment. Risk index values from RI and MCS provide valuable insights in the contamination profile of the river, indicating the studied river is currently under low ecological risk for the studied heavy metals. This study can be utilized to assess the susceptibility of the river sediment to heavy metal pollution near an urban core, and to have a better understanding of the contamination profile of a river.

Evaluation on Characteristics of Heavy Metal Spatial Pollution in Farmland Soils along the Bijiang River

2013 ◽  
Vol 295-298 ◽  
pp. 1586-1593
Author(s):  
Xiao Qing Zhao ◽  
Hong Hui Yang ◽  
Jian Chen
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Spatial Variation ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Pollution Index ◽  
Pollution Level ◽  
Zinc Deposit ◽  
Farmland Soils ◽  
Lead Zinc

Based on the farmland soils along the Bijiang River, a main tributary of the international Lantsang-Mekong River flowing through the Jinding Lead-Zinc Deposit, this dissertation makes analyses on the pollution characteristics of spatial variation in farmland soils by adopting the soil sampling and testing analysis and applying single-factor pollution index (SPI) evaluation and Nemerow composite pollution index (NCPI) evaluation. The results indicate that: (1) In accordance with Environmental Quality Standard for Soils (II), the content of Cd contained in the farmland soils has severely exceeded the standard in a large scale, followed by Pb and Zn. However, the content of As is maintained within the specified standard; (2)The SPI values of soils are in the following sequence: Cd＞Zn＞Pb＞As. The pollution level caused by the heavy metal “Cd” to the farmland soils is extremely heavy in a wide range, and a majority of the farmlands are heavily polluted by Zn. The farmlands with moderate pollution by Pb are centered at Plot 2 in the deposit, and only a few farmland soils are moderately polluted by As at Plot 2 in the deposit;(3) Based on the NCPI, the results indicate that the NCPI of the farmland soils has reached to the degree of heavy pollution; (4) It is indicated based on the RPI evaluation that the RPI values of As, Cd, Pb and Zn contained in the farmland soils have exceeded the standard in the following sequence: Pb＞Zn＞Cd＞As, which illustrates that during the development of Jinding Lead-Zinc Deposit in Lanping County, the heavy metals imposing the most profound influence on the soil pollution are Pb and Zn. The heavy metal pollution in the farmland soils from the upper reaches to the lower reaches of the Bijiang River is not only caused by the development of Jinding Lead-Zinc Deposit in Lanping County, but is also associated with its high soil background value;(5) There is a remarkable spatial variation of heavy metal pollution in farmland soils from the upper reaches to the lower reaches of the Bijiang River. Both the SPI and the NCPI values of heavy metals in the soils within the deposit at the upper reaches of the Bijiang River are the lowest; the pollution index of the soils closest to the deposit are the highest, and the pollution index of the soils with a certain distance from the deposit drops swiftly; the pollution index of Plot 4 rises to a certain degree at the middle reaches, and gradually ascends near the Yunlong County seat at Plot 5, however, with a comparatively small growth rates.

Optimal Regulation of Rural Ecosystem Pollution

1977 ◽  
Vol 9 (11) ◽  
pp. 1281-1289 ◽  
Author(s):  
J Talavage
Keyword(s):  
Heavy Metal ◽  
Computer Simulation ◽  
Dynamic Programming ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Pollution Abatement ◽  
Optimization Procedure ◽  
Pollution Level ◽  
Computer Simulation Model ◽  
Rural Ecosystem

A methodology is described which can aid in the planning of pollution abatement schedules. The methodology consists of a system dynamics computer-simulation model of the polluted ecosystem, and a powerful dynamic programming optimization procedure which causes the pollution level in the model to be reduced in some optimal manner. An application of the methodology is shown to a situation of heavy metal pollution in northwest Indiana.

Active biomonitoring of heavy metal pollution using Rosa rugosa plants

2007 ◽  
Vol 149 (2) ◽  
pp. 239-245 ◽  
Author(s):  
Gian Lorenzo Calzoni ◽  
Fabiana Antognoni ◽  
Elena Pari ◽  
Paolo Fonti ◽  
Antonio Gnes ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Rosa Rugosa ◽  
Active Biomonitoring

scholarly journals SPATIAL DISTRIBUTION, POLLUTION, AND HEALTH RISK ASSESSMENT OF HEAVY METAL IN INDUSTRIAL AREA SOILS OF ULAANBAATAR, MONGOLIA

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 123-133
Author(s):  
P. Oyunbat ◽  
O. Batkhishig ◽  
B. Batsaikhan ◽  
F. Lehmkuhl ◽  
M. Knippertz ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Spatial Distribution ◽  
Health Risk ◽  
Soil Pollution ◽  
Ecological Risk ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Pollution Index ◽  
Industrial Area ◽  
Pollution Level

Abstract. The heavy metal pollution of urban soil of industrial area and its impact on human healths becoming one of the environmental problems in Ulaanbaatar city of Mongolia. The purpose of this study was to determine spatial distribution and health risk of heavy metal pollution in soils surrounding area of leather processing factory and wastewater treatment plants (WWTP) of Ulaanbaatar city. Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal (As, Zn, Pb, Cd, Cr, Cu) concentrations of topsoils. The average concentrations of Cr, Ni, Pb, Zn, Cu and As were 1986.9, 110.5, 111.0, 110.5, 53.5, 16.4 mg/kg, respectively. According to result as the soil pollution index with spatial distribution, a high pollution level for Cr while Zn, Cu and Pb have medium pollution levels. The soil pollution index (PI) values of heavy metals of study areas are, following descending orders Cr > Zn > Cu > Pb > As > Ni. The potential ecological risk of Cr, Cu, Pb, As indicated high ecological risk in the study area. The Hazard index values for almost all the metals were higher than 1, it is indicating a carcinogenic risk for children and adults. The risk index values of two metals (Cr, As) were contribute to a higher risk of development of cancer in humans. Heavy metal contamination can occur when soil particles are swept away from the initial pollution areas by the wind. Therefore, it is necessary to take measures to reduce soil pollution and encourage rehabilitation.

scholarly journals Study of Pb Heavy Metal Pollution Level on Tannin Content of Seaweed (Kappaphycus alvarezii) in Bluto and Talango Sea Waters, Sumenep, East Java

2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Catur Pujiono ◽  
Akhmad Taufiq Mukti ◽  
Woro Hastuti Satyantini
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Kappaphycus Alvarezii ◽  
Pollution Level ◽  
Tannin Content ◽  
Significant Difference ◽  
The Relationship

Euchema cottoni or Kappaphycus alvarezii is one type of seaweeds that is widely cultivated in Indonesia. Water pollution caused by the accumulation of Pb heavy metals will affect the seaweed to grow and develop. This study is aimed to determine the tannin levels in K. alvarezii and the relationship of Pb heavy metal pollution level with tannin levels in K. alvarezii in different waters. This study used an observational experiment, and samples were taken from two different locations with 4 stations in each. From each sample in both locations, K. alvarezii was taken and was then measured for the tannin levels, water quality, and heavy metals (Pb) in water and in K. alvarezii. The results were analyzed at the Laboratory of PT. Sucofindo and the Laboratory of Testing Service Unit, Airlangga University Surabaya. The data were analyzed using a statistical test in the form of a t-test to determine the differences in samples in both waters, and a C-square test was used to determine the relationship between PB and tannin levels in K. alvarezii. The results showed that the level of Pb heavy metal pollution in the two waters did not show a significant difference due to water quality which was quite similar in both locations. Moreover, the tannin content in K. alvarezii in Bluto waters (0.053±0.004%) was higher than that in Talango waters (0.020±0.009%). Meanwhile, a t-test showed a significant difference in seaweed tannins in both waters. The relationship between Pb heavy metal pollution and tannins of seaweed in Bluto and Talango waters was that they did not affect each other, and tannin concentration was more influenced by chemical oxygen demand (COD), salinity of both waters, and the cultivation methods used.

scholarly journals Evaluation of Heavy Metal Pollution in Shallow Groundwater of Farmland in Huaibei Plain, China

2021 ◽  
Vol 267 ◽  
pp. 02009
Author(s):  
Yong Zhang ◽  
Xuanxia Wang
Keyword(s):  
Heavy Metal ◽  
Health Risk ◽  
Health Risks ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Shallow Groundwater ◽  
Pollution Index ◽  
Pollution Level ◽  
Index Method ◽  
Comprehensive Index

In order to understand the characteristics of heavy metal pollution in shallow groundwater in farmland in Huaibei Plain, 69 samples were collected from typical farmland areas in Xiaoxian County to determine the content of heavy metal elements such as Cr, Zn, Cu, Cd, and Ni. The single-factor pollution index method and Nemerow comprehensive index method are used to evaluate and analyze the pollution degree and the health risk assessment method is used to explore the health risk level. The results show that the concentrations of Cr, Zn, Cu, Cd and Ni were respectively 1.27μg∙L-1~268.78μg∙L-1, 0.45μg∙L-1~ 266.1μg∙L-1, 1.77μg∙L-1~ 29.8μg∙L-1, 0.10μg∙L-1~ 21.54μg∙L-1 and 0.9μg∙L-1~ 252.85μg∙L-1. The Nemerow comprehensive index of each heavy metal element is 0.031~5.507, and the pollution degree is Ni>Cr>Cd>Zn>Cu. The Nemerow comprehensive pollution index of each sampling point is 0.251~9.325, with an average value of 1.934. The overall value is 9.523, and the pollution level is extremely poor. The overall health risk is at a risk-free health level. There are 19 samples which the carcinogenic risk index of the Cr is greater than 10-4, and the number of samples with health risks accounts for 27.5%. Cr is the main source of heavy metal health risks in shallow groundwater in farmland.

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