武汉市城乡交错带土壤重金属空间分布特征
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摘要
城市扩张、工业化以及农业集约化的发展影响着土壤环境质量,特别是土壤中重金属的输入会对土壤的物理化学性质产生一定的影响,它们或被淋洗到地下水或者通过空气悬浮物扩散,潜在的危及人类的生命健康。城市土壤中重金属污染源不仅量多,而且种类繁多,研究城市或者郊区土壤重金属的分布状况和来源途径可为保护生态环境和建设宜居环境提供一定的理论依据。
本研究首先利用景观破碎度和多样性指数(SHDI)理论,将研究区划分为三个部分:城区、城乡交错带、农村,确定112样点,每样点按0-10cm,10-20cm,20-40cm三层分别取样。分析了样品中六种重金属(Cd、Cu、Ni、Pb、Zn、Mn)和两常规元素(Ca、Mg)的全量值,对八种金属进行空间分布分析和因子分析(FA),得出重金属在城区、城乡交错带、农村的水平、垂直分布状况以及重金属的大致来源等结论,主要结论如下:
(1)重金属空间分布特征。一是水平方向上空间分布,对每个研究区的三个层次均进行了描述性统计,与国家背景值对比,同时也进行了研究区之间的对比。二,垂直分布,对每个研究区三个不同厚度层次上的浓度值进行了比较。结果为:重金属Cd超出国家一级标准9倍,Cu也超出50%以上,Ni、Pb、Zn、Mn含量值与国标基本持平;城乡交错带土壤重会属含量值高于城区和农村。垂直结构分析表明:城区土壤中重金属主要积聚在0-10cm,城乡交错带和农村土壤在10-20cm呈现最高值。
(2)重金属空间分布预测。对原始数据进行K-S正态检验,对不符合正态分布的数据进行log变换,再做K-S正态检验。然后对比数据在不同插值方法(普通克里格法、反距离权重法、RBF神经网络法)下的误差,误差越小,插值方法越合适。对于每种重金属数据分别选出合适的变换方法和插值方法,在ArcGIS得到各重金属的空间预测图。对比三个层次上的预测图,结合垂直分析的结果,得出结论如下,六种重金属主要集中在城乡交错带上,城区,农村分布较少。重金属在0-10cm层次上的分布非常零散,且大多分布在城乡交错带。而Cd、Cu、Ni、Pb四重金属元素最明显的特点是在城乡交错带的含量较高,它们主要分布在城乡交错带的三个集中区域。
(3)重金属来源分析。根据Celine等的理论,因子分析(FA)中重金属元素和常规元素的是否在同一公因子通常被用来判断重金属的来源,本研究利用因子分析来判断重金属来自人为作用还是自然母质。本研究对三个研究区,分别按三个层次进行因子分析。结果表明:城区土壤0-10cm层次上重金属主要受交通和生活等人为活动因素作用,10-20cm和20-30cm厚度上的分布则受母质分布影响,城区土壤重金属表面积聚;城乡交错带土壤中0-10cm的有效量重金属易被淋溶到10-20cm,致使后者积聚,说明城乡交错带土壤重金属易受淋溶作用影响。农村中样品大多采自于荒地,元素有沉降的可能性,且土壤中重金属有向根际土壤迁移的趋势,所以土层1中重金属元素的外来性不是很明显,土层2重金属明显增高(可以从垂直分析结果看出),土层3由于采样深度的原因,体现出很好的原始性。
Urban expansion, industrialization, as well as the development of agricultural intensification affects soil environmental quality. In particular the input of heavy metals in soil on soil can affect soil physical and chemical properties. They also harm human health throught water and air which contain heavy metal from soil.In urban soil there are lots of metals which from many kinds of sources, the study of distribution and sources of soil heavy metals can provide a theoretical basis to protect the ecological environment and construct suitable living environment in some sense.
In this study, we use landscape fragmentation and diversity index (SHDI) theory to divide study area into three parts: urban, peri-urban interface and rural areas quantificationally. 112 samples are sampled in three places, 0-10cm, 10-20cm, 20-40cm, respectively. We analyse six heavy metals (Cd, Cu, Ni, Pb, Zn, Mn) and two conventional elements (Ca, Mg) in soil samples. Spatial analysis and Factor Analysis (FA) are done to interpret the spatial distribution of heavy metals. In this paper, the main conclusions as follows:
(1) Spatial distribution of heavy metals. Firstly, the analysis of horizontal direction, descriptive statistics are carried out at three levels, there are not only comparisons with the national background values, but also comparisons between study areas. Results show that: heavy metal Cd exceeds 9 times of the national standard, Cu also exceed 50%, Ni, Pb, Zn, Mn content are the same as GB basically; soil heavy metal content in peri-urban interface is higher than urban and rural areas. Vertical analysis showed that: heavy metals in urban soil mainly centralize in 0-10cm, as peri-urban interface and rural areas, 10-20cm.
(2) Spatial prediction analysis of heavy metals. Firstly original Data are carried out K-S normality test, as to the data of Non-normal distribution, log transformation is done. Then we compare errors between different interpolation methods, ordinary kriging(OK), inverse distance weighting method(IDW), RBF neural network(RBF), to decide the excellent interpolation method, the smaller the error, the better the method.The spatial prediction map of different metals in three levels are generated in ArcGIS. In the help of vertical analysis, we can come to the conclusion, six heavy metals mainly concentrated in the urban, but rarely in peri-urban interface and rural areas. Map shows, the distribution of heavy metals in level 0-10cm is very fragmented, and mainly located in peri-urban interface. The most obvious characteristic of heavy metals Cd, Cu, Ni, and Pb is there is a highest value in peri-urban interface, and they concentrate in three special regions.
(3) Source analysis of heavy metals based on Factor Analysis. According to Celine's theory, in factor analysis, whether heavy metals and conventional elements are in the same common factor is often used to determine the source of heavy metals. In this study, factor analyses are carried out in three levels of three study areas, respectively. Results showed that: In City, heavy metals of level 0-10cm is mainly affected by traffic and life factors, which are primary human activities, the distribution of heavy metals in level 10-20cm and 20-30cm is determined by parent material, urban heavy metals accumulate on soil surface mainly.Whereas heavy metals in peri-urban interface soil surface can easily leach to 10-20cm, which has a higher value. We can explain the the effects of rain leaching on heavy metals in soil. Most of the samples in rural areas are collected from the badlands, and there is a trend that heavy metals in the soil transfer to rhizosphere slowly, so the Man-made sources of heavy metals in soil layer 1 of is not very clear, but heavy metals in soil 2 are significantly increased, which can be seen in vertical analysis; as a result of sample depth, heavy metals in layer 3 reflects good original.
本研究首先利用景观破碎度和多样性指数(SHDI)理论,将研究区划分为三个部分:城区、城乡交错带、农村,确定112样点,每样点按0-10cm,10-20cm,20-40cm三层分别取样。分析了样品中六种重金属(Cd、Cu、Ni、Pb、Zn、Mn)和两常规元素(Ca、Mg)的全量值,对八种金属进行空间分布分析和因子分析(FA),得出重金属在城区、城乡交错带、农村的水平、垂直分布状况以及重金属的大致来源等结论,主要结论如下:
(1)重金属空间分布特征。一是水平方向上空间分布,对每个研究区的三个层次均进行了描述性统计,与国家背景值对比,同时也进行了研究区之间的对比。二,垂直分布,对每个研究区三个不同厚度层次上的浓度值进行了比较。结果为:重金属Cd超出国家一级标准9倍,Cu也超出50%以上,Ni、Pb、Zn、Mn含量值与国标基本持平;城乡交错带土壤重会属含量值高于城区和农村。垂直结构分析表明:城区土壤中重金属主要积聚在0-10cm,城乡交错带和农村土壤在10-20cm呈现最高值。
(2)重金属空间分布预测。对原始数据进行K-S正态检验,对不符合正态分布的数据进行log变换,再做K-S正态检验。然后对比数据在不同插值方法(普通克里格法、反距离权重法、RBF神经网络法)下的误差,误差越小,插值方法越合适。对于每种重金属数据分别选出合适的变换方法和插值方法,在ArcGIS得到各重金属的空间预测图。对比三个层次上的预测图,结合垂直分析的结果,得出结论如下,六种重金属主要集中在城乡交错带上,城区,农村分布较少。重金属在0-10cm层次上的分布非常零散,且大多分布在城乡交错带。而Cd、Cu、Ni、Pb四重金属元素最明显的特点是在城乡交错带的含量较高,它们主要分布在城乡交错带的三个集中区域。
(3)重金属来源分析。根据Celine等的理论,因子分析(FA)中重金属元素和常规元素的是否在同一公因子通常被用来判断重金属的来源,本研究利用因子分析来判断重金属来自人为作用还是自然母质。本研究对三个研究区,分别按三个层次进行因子分析。结果表明:城区土壤0-10cm层次上重金属主要受交通和生活等人为活动因素作用,10-20cm和20-30cm厚度上的分布则受母质分布影响,城区土壤重金属表面积聚;城乡交错带土壤中0-10cm的有效量重金属易被淋溶到10-20cm,致使后者积聚,说明城乡交错带土壤重金属易受淋溶作用影响。农村中样品大多采自于荒地,元素有沉降的可能性,且土壤中重金属有向根际土壤迁移的趋势,所以土层1中重金属元素的外来性不是很明显,土层2重金属明显增高(可以从垂直分析结果看出),土层3由于采样深度的原因,体现出很好的原始性。
Urban expansion, industrialization, as well as the development of agricultural intensification affects soil environmental quality. In particular the input of heavy metals in soil on soil can affect soil physical and chemical properties. They also harm human health throught water and air which contain heavy metal from soil.In urban soil there are lots of metals which from many kinds of sources, the study of distribution and sources of soil heavy metals can provide a theoretical basis to protect the ecological environment and construct suitable living environment in some sense.
In this study, we use landscape fragmentation and diversity index (SHDI) theory to divide study area into three parts: urban, peri-urban interface and rural areas quantificationally. 112 samples are sampled in three places, 0-10cm, 10-20cm, 20-40cm, respectively. We analyse six heavy metals (Cd, Cu, Ni, Pb, Zn, Mn) and two conventional elements (Ca, Mg) in soil samples. Spatial analysis and Factor Analysis (FA) are done to interpret the spatial distribution of heavy metals. In this paper, the main conclusions as follows:
(1) Spatial distribution of heavy metals. Firstly, the analysis of horizontal direction, descriptive statistics are carried out at three levels, there are not only comparisons with the national background values, but also comparisons between study areas. Results show that: heavy metal Cd exceeds 9 times of the national standard, Cu also exceed 50%, Ni, Pb, Zn, Mn content are the same as GB basically; soil heavy metal content in peri-urban interface is higher than urban and rural areas. Vertical analysis showed that: heavy metals in urban soil mainly centralize in 0-10cm, as peri-urban interface and rural areas, 10-20cm.
(2) Spatial prediction analysis of heavy metals. Firstly original Data are carried out K-S normality test, as to the data of Non-normal distribution, log transformation is done. Then we compare errors between different interpolation methods, ordinary kriging(OK), inverse distance weighting method(IDW), RBF neural network(RBF), to decide the excellent interpolation method, the smaller the error, the better the method.The spatial prediction map of different metals in three levels are generated in ArcGIS. In the help of vertical analysis, we can come to the conclusion, six heavy metals mainly concentrated in the urban, but rarely in peri-urban interface and rural areas. Map shows, the distribution of heavy metals in level 0-10cm is very fragmented, and mainly located in peri-urban interface. The most obvious characteristic of heavy metals Cd, Cu, Ni, and Pb is there is a highest value in peri-urban interface, and they concentrate in three special regions.
(3) Source analysis of heavy metals based on Factor Analysis. According to Celine's theory, in factor analysis, whether heavy metals and conventional elements are in the same common factor is often used to determine the source of heavy metals. In this study, factor analyses are carried out in three levels of three study areas, respectively. Results showed that: In City, heavy metals of level 0-10cm is mainly affected by traffic and life factors, which are primary human activities, the distribution of heavy metals in level 10-20cm and 20-30cm is determined by parent material, urban heavy metals accumulate on soil surface mainly.Whereas heavy metals in peri-urban interface soil surface can easily leach to 10-20cm, which has a higher value. We can explain the the effects of rain leaching on heavy metals in soil. Most of the samples in rural areas are collected from the badlands, and there is a trend that heavy metals in the soil transfer to rhizosphere slowly, so the Man-made sources of heavy metals in soil layer 1 of is not very clear, but heavy metals in soil 2 are significantly increased, which can be seen in vertical analysis; as a result of sample depth, heavy metals in layer 3 reflects good original.
引文
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