国土整治中关于土地重金属污染生态修复的问题与对策

土地整治一般包括土地回收、土壤修复、植被保护等方面。在进行土地整治时,相关人员需要考虑场地条件、污染情况和生态修复要求,并结合当地的实际情况选择最合适的措施。对于已经受到重金属污染的土壤,通常需要采用一些处理和修复方法,包括物理清理、化学清理和生物清理等。物理清理主要是使用机械或者物理方法清除污染物质;化学清理则是使用化学试剂或肥料降低土壤中的重金属含量;生物清理是利用生物物质或微生物分解土壤中的污染物。总之,土地重金属污染是一个复杂的问题,需要相关人员根据实际情况选择最合适的方法和措施。同时,在国土整治中,工作人员也需要综合考虑多方面的因素,以确保土地的可持续利用和环境保护。

基于多传感器的土地重金属污染范围测量研究

为准确测量土地重金属污染情况,给后续治理提供帮助,研究设计了一种基于多传感器的土地重金属污染范围测量方法。先制备电沉积金纳米生物传感器,采用溶出法进行扫描测量,然后分析对于不确定的溶质影响,建立浓度与峰值的线性回归法,推导溶液浓度与峰值之间的关系式,最后建立重金属污染迁移传播模型,采用多传感器融合方法将检测结果融合,实现土地重金属污染范围测量。实验结果表明,所提方法能够较为准确地测量出重金属污染范围,并在Cu^(2+)、Zn^(2+)、Cr^(6+)与Cd^(2+)四个重金属含量测量上具有较高的准确性,进一步验证了该方法的测量效果。

国土整治中关于土地重金属污染生态修复的问题与对策

在土地整治项目中,处理土地的重金属污染成为一项紧迫的任务。这种污染通常由诸如砷、汞、镉、铅等重金属元素引起,当这些元素渗入土壤和地下水后,可能对植物、动物乃至人类健康构成威胁。可见,重金属污染程度的加剧会直接影响土地的品质与其使用价值,因此,此类土地亟须进行生态恢复以恢复其原有价值。本文将详细分析国土整治中土地重金属污染生态修复的相关问题,并提出相应的解决对策,以供参考。

植物修复技术在重金属污染土壤修复中的应用

如何将被污染的土地再生利用,对污染的土地和植物等进行修复,成为当今世界需要面对和解决的一项重要难题,而利用绿色植物修复重金属污染土壤就是一项新兴的技术。文章主要阐述了重金属污染土壤中植物修复技术的相关问题,并提出提高植物修复技术的相关措施。

Effect of Heavy Metal Pollution on Potassium Behavior in Typic Udic Ferrisol

The indirect influence of heavy metal contamination of soil on nutrient availability, an important aspect of soil quality, may need to be taken into consideration when determining overall effects of heavy metals. A laboratory experiment was performed to study the effects of combined pollution of Cu, Ph, Zn and Cd on soil K status as indicated by chemical fractions, adsorption-desorption and quantity/intensity (Q/I) relationship of K in a Typic Udic Ferrisol (generally called red soil), by employing uniform design and single factor design. Compared to the control, content of exchangeable K was decreased, but that of soluble K increased in the samples contaminated with heavy metals. Due to heavy metal pollution, potassium adsorption was reduced by 5% to 22%, whereas the desorption percentage of adsorbed K increased by 2% to 32%. The Q/I curves shifted downward, potassium buffering capacity (PBCK) decreased, and equilibrium activity ratio values (ARoK) increased with increasing heavy metal pollution. These influences followed the sequences of Ph>Cu>Zn and combined pollution>single one. Displacement of K from canon exchange sites and decrease in soil CEC due to heavy metals should be responsible for the changes of soil K behaviours. The findings suggest that heavy metal pollution of soil might aggravate the degradation of soil K fertility by decreasing K adsorption and buffering capacity and increasing desorption.

Heavy Metal Distribution Map in Soil by Using GIS Techniques

A detailed investigation was conducted to understand the contamination characteristics and distributions of heavy metal pollution in terms of contributions of the heavy metal concentrations as mg/kg ofCd, Cr, Cu, Ni, Zn, Pb, Fe and Mn in the urban soil in Eskisehir city center. The amount of these heavy metals were determined from 15 soil sample points collected within urban area and every sample point included 6 separated samples for chemical analyses. The results indicated that concentration values of all metals except Ni and Cr in soils were below the risky limit pollution values which are recommended by Turkey Ministry of Environment and Forestry in some sample points. Spatial distribution maps were created and recoded, in terms of these heavy metals concentrations as contribution to heavy metal pollution in soil, through Geographical Information Systems techniques. As a result, risky areas were modeled in terms of contamination of heavy metal and it is shown that, every different risky area can be interpreted based on buildings in city center quickly and easily.

Analysis of Soil Heavy Metal Pollution in Hechuan Wetland

Soil samples were collected from Hechuan wetland and digested by the national standard method. The contents of Pb, Cd, Cr, Cu, Zn and Mn in the wetland soil were determined, and the degree of soil heavy metal pollution was estimated by single-factor pollution index, root-mean-square comprehensive pollution index and geo-accumulation pollution index methods. The results showed that the wetland in the sampling range was seriously polluted by heavy metals, mainly by heavy metal Cd, while the effects from other heavy metals were relatively less.

Spatial Distribution of Magnetic Properties and Selected Heavy Metals in Calcareous Soils as Affected by Land Use in the Isfahan Region,Central Iran

Anthropogenic activities have caused the accumulation of heavy metals in the soil environment. Pollution of the soils significantly reduces environmental quality and affects human health. In many recent studies, magnetic susceptibility ts have been used for pollution monitoring. The objective of this research was to determine the spatial variability of magnetic properties and selected heavy metals and the effect of land use on their variability in the surface soils of the Isfahan region, Central Iran. A total of 158 composite surface （0-5 cm） samples of calcareous soils were collected from an area of about 700 km2, located along a cross-border transect from Isfahan City to a steel plant, covering urban, industrial, agricultural, and uncultivated land uses. Concentrations of copper （Cu）, zinc （Zn）, lead （Pb）, manganese （Mn）, iron （Fe）, nickel （Ni）, chromium （Cr）, and cobalt （Co） and magnetic parameters, magnetic susceptibility at low frequency （xlf）, natural remanent magnetization （NRM）, saturation isothermal remanent magnetization （SIRM）, and isothermal remanent magnetization at the field of 100 mT （IRM100mT） and the backfield of 100 mT （IRM-100mT）, were measured in all the soil samples. Results showed that magnetic susceptibility in the urban and industrial land topsoils （0-5 cm） samples was significantly higher than that in the agricultural and uncultivated land soils in the study area. Concentrations of Cu, Zn, Pb, Mn, and Fe were positively correlated with magnetic properties （xlf, IRM100mT, SIRM, IRM-100mT, and NRM）, which could be attributed to their inputs from traffic emissions and industrial activities at the study sites. Ni and Cr concentrations showed significant negative correlations with magnetic properties. No significant correlation was found between Co concentration and magnetic parameters. The Tomlinson pollution load index （PLI） showed significant correlation with the magnetic properties （xlf, IRM100mT, SIRM, IRM-100mT, and NRM）. The spatial distribution of the selected heavy metals and xlf in the study area suggested that activities at the urban and industrial land sites caused greater pollution as compared to that at the study sites of other land uses. The concentrations of Cu and Zn seemed to have been affected by anthropogenic sources, whereas Ni, Cr, and Co were mainly controlled by natural sources in the study area. Moreover, the concentrations of soil Pb and Fe in the study area could be affected by both lithologic and anthropogenic sources. The magnetic parameters appeared to be a proxy measure for the degree of heavy metal contamination and could be a potential method for the detection and mapping of contaminated soils.

Spatial Distribution Patterns and Potential Sources of Heavy Metals in Soils of a Crude Oil-Polluted Region in China

Twenty-two soil samples were collected at the subregional scale （50 km2） around Gudao Town, a typical oil-producing region of the Shengli Oilfield in the Yellow River Delta, China to determine the spatial distribution patterns and potential sources of heavy metals in soils of crude oil-polluted regions. The concentrations of total petroleum hydrocaxbons （TPHs） and heavy metals as well as other soil properties were determined and the enrichment factor values were calculated for the heavy metals measured. Principal component analysis （PCA） and cluster analysis （CA） were used to estimate potential sources contributing to the concentrations of heavy metals in the soils. The results revealed that the soils were slightly alkaline （pH = 7.33-8.05） and high in salinity （1.43-41.30 g kg-1）, TPHs （0.51 28.40 g kg-1） and organic matter （1.74-31.50 g kg-1）. The mean concentrations of the measured heavy metals Cu, Zn, Pb, Cd, Cr, Ni and V were 18.4, 78.2, 20.8, 0.19, 56.6, 26.3 and 62.1 mg kg-1, respectively. Although the concentrations of all the metals measured in this study were not high enough to exceed the national control standards, there was a significant enrichment of Cd in the study area and Zn and Ni were in the category of deficiency to minimal enrichment. The spatial distribution patterns of Cu, Cr, Ni and V were similar and partially affected by oil exploitation and petroleum hydrocarbon spills. Potential sources of Cr, Ni, V and Cu in the soils were both natural sources and petroleum hydrocarbon spills, while Zn, Pb and Cd were probably from anthropogenic sources such as farming activities and traffic.

Source Apportionment of Heavy Metals in Soils Using Multivariate Statistics and Geostatistics

The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.