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High-concentration areas of soil heavy metals exist in ecological functional protection zones of Southwest China. To investigate their potential pollution risks and influencing factors, this study selected soils in the Xuanwei region of Yunnan Province as the research subject. Combining geographical, geological, and anthropogenic activity data, the content characteristics of eight heavy metal elements were analyzed in 1487 surface soil samples and 374 deep soil samples. The geo-accumulation index and potential ecological risk index were used to assess the potential pollution risks of surface soils, while principal component analysis(PCA)and geographical detector methods were employed to identify influencing factors. The results revealed that heavy metals in both surface and deep soils were enriched compared to the A-layer and C-layer background values of Chinese soils. Most heavy metals also exhibited enrichment relative to the A-layer and C-layer background values of Yunnan Province. Cd, Hg, and Pb posed relatively high potential pollution risks, whereas Cu, Cr, Ni, Zn, and As showed lower risks. The main influencing factors for heavy metal enrichment included geological background, clay minerals, organic matter, mining activities, and topography. Synergistic effects of multiple factors could exacerbate heavy metal enrichment, while pH, CaO, Light(light index), and WIG exhibited minimal impacts.

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我国西南生态功能保护区内存在土壤重金属高含量区,为探究其潜在污染风险及影响因素,选择云南省宣威地区土壤为研究对象,结合地理、地质、人类活动等相关资料,对区内表层组合土壤样品1487份、深层组合土壤样品374份中的8种重金属元素含量特征进行了分析,分别利用地累积指数法和潜在生态危害指数法评价了表层组合土壤的潜在污染风险,采用主成分分析法和地理探测器对其影响因素进行了解析.结果显示,相对于中国土壤A层、C层背景值研究区表、深层土壤中重金属均显示富集;相对于云南省A层、C层土壤背景值大部分重金属亦显示富集;Cd、Hg、Pb存在较高的潜在污染风险,Cu、Cr、Ni、Zn、As则潜在污染风险较低;地质背景、黏土矿物、有机质、矿业活动、地形地貌是土壤中重金属元素的主要影响因素,多影响因素的协同作用可能会使重金属富集加剧,pH值、CaO、Light(灯光指数)、WIG对重金属富集的影响则较小.

, correspAuthors=郭志娟, authorNote=null, correspAuthorsNote=
* 责任作者,高级工程师,
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韩伟(1985-),男,河北保定人,高级工程师,硕士,主要研究方向为环境地球化学和勘查地球化学.发表论文27篇..

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韩伟(1985-),男,河北保定人,高级工程师,硕士,主要研究方向为环境地球化学和勘查地球化学.发表论文27篇..

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韩伟(1985-),男,河北保定人,高级工程师,硕士,主要研究方向为环境地球化学和勘查地球化学.发表论文27篇..

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The conceptual model of mercury's mountain altitude effect [C]. The 7th National Conference on Environmental Chemistry. 2013:19-20., articleTitle=The conceptual model of mercury's mountain altitude effect, refAbstract=null)], funds=[Fund(id=1241057226132091718, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, awardId=2019QZKK020404, language=CN, fundingSource=第二次青藏高原综合科学考察研究(2019QZKK020404), fundOrder=null, country=null), Fund(id=1241057226245337943, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, awardId=DD20190522, language=CN, fundingSource=乌蒙山区土地质量地球化学调查(DD20190522), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241057215642137488, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, xref=1., ext=[AuthorCompanyExt(id=1241057215646331793, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057215642137488, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Science, Langfang 065000, China), AuthorCompanyExt(id=1241057215654720402, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057215642137488, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国地质科学院地球物理地球化学勘查研究所,河北 廊坊 065000)]), AuthorCompany(id=1241057215751189402, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, xref=2., ext=[AuthorCompanyExt(id=1241057215759578011, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057215751189402, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.Key Laboratory of Geochemical Exploration, Ministry of Natural Resources, Langfang 065000, China), AuthorCompanyExt(id=1241057215763772316, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057215751189402, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.自然资源部地球化学探测重点实验室,河北 廊坊 065000)]), AuthorCompany(id=1241057215872824231, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, xref=3., ext=[AuthorCompanyExt(id=1241057215885407146, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057215872824231, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.Geochemical Research Center of Soil Quality, China Geological Survey, Langfang 065000, China), AuthorCompanyExt(id=1241057215893795754, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057215872824231, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.中国地质调查局土地质量地球化学调查评价研究中心,河北 廊坊 065000)]), AuthorCompany(id=1241057216061567921, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, xref=4., ext=[AuthorCompanyExt(id=1241057216086733749, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057216061567921, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.UNESCO International Center on Global-scale Geochemistry, Langfang 065000, China), AuthorCompanyExt(id=1241057216103510966, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, companyId=1241057216061567921, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.联合国教科文组织全球尺度地球化学国际研究中心,河北 廊坊 065000)])], figs=[ArticleFig(id=1241057222181057051, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Fig.1, caption=Geographical location of the study area, figureFileSmall=b3DOTsRB6sccSC1IdjgIBQ==, figureFileBig=YOiFaPCUuF0MjwdGUlTWNA==, tableContent=null), ArticleFig(id=1241057222298497576, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=图1, caption=研究区地理位置

1:省界;2:主要河流;3:西南喀斯特地区水土保持生态功能区;4:珠江源水源涵养生态功能区;5:其他生态功能区;6:表层土壤分析点位

, figureFileSmall=b3DOTsRB6sccSC1IdjgIBQ==, figureFileBig=YOiFaPCUuF0MjwdGUlTWNA==, tableContent=null), ArticleFig(id=1241057222663402066, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Fig.2, caption=Characteristics of heavy metal contents in different land use types, figureFileSmall=o6AgorzqHLvH3UW1RHcFww==, figureFileBig=iximW6OSf1gX2osG0SvHHg==, tableContent=null), ArticleFig(id=1241057222768259685, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=图2, caption=不同土地利用类型土壤中重金属含量特征

a:林地;b:耕地;c:采矿用地;d:草地;e:城镇用地;f:裸地.

, figureFileSmall=o6AgorzqHLvH3UW1RHcFww==, figureFileBig=iximW6OSf1gX2osG0SvHHg==, tableContent=null), ArticleFig(id=1241057222910866040, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Fig.3, caption=Percentage grading of heavy metal ecological risk index, figureFileSmall=x6dX7gh4wI9OGyvlq2qEYQ==, figureFileBig=0Naoo2h17WLqh2Y6zJcu1Q==, tableContent=null), ArticleFig(id=1241057223015723655, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=图3, caption=潜在生态危害指数分级百分比, figureFileSmall=x6dX7gh4wI9OGyvlq2qEYQ==, figureFileBig=0Naoo2h17WLqh2Y6zJcu1Q==, tableContent=null), ArticleFig(id=1241057223175107219, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Fig.4, caption=Spatial distribution of potential ecological risk index grading, figureFileSmall=nEe1N4gw+dm7oCYXI8IOgQ==, figureFileBig=eD0RluhAzeI68t/z5f2P7w==, tableContent=null), ArticleFig(id=1241057223363850926, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=图4, caption=潜在生态危害指数分级分布, figureFileSmall=nEe1N4gw+dm7oCYXI8IOgQ==, figureFileBig=eD0RluhAzeI68t/z5f2P7w==, tableContent=null), ArticleFig(id=1241057223548400326, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Table 1, caption=

Classification criteria of potential ecological risk index

, figureFileSmall=null, figureFileBig=null, tableContent=
Ei风险等级RI值风险等级
Ei<40轻微RI<100轻微
40≤Ei<80中等100≤RI<200中等
80≤Ei<160较高200≤RI<400较高
160≤Ei<320400≤RI<800
Ei≥320很高Ei≥800很高
), ArticleFig(id=1241057223661646547, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=表1, caption=

潜在生态危害指数分级

, figureFileSmall=null, figureFileBig=null, tableContent=
Ei风险等级RI值风险等级
Ei<40轻微RI<100轻微
40≤Ei<80中等100≤RI<200中等
80≤Ei<160较高200≤RI<400较高
160≤Ei<320400≤RI<800
Ei≥320很高Ei≥800很高
), ArticleFig(id=1241057223774892771, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Table 2, caption=

Statistics of soil heavy metals in the study area(mg/kg)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素表层土壤(n=1487)深层土壤(n=374)
均值±标准差变化系数范围中国土壤背景值云南背景值均值±标准差变化系数范围中国土壤背景值云南背景值
As18.8±23.11.232.03~33811.218.418.0±21.51.191.38~25011.525.4
Cd1.81±0.970.540.48~11.10.0970.2180.67±1.342.020.08~13.60.0840.155
Cr196±84.70.4348.9~5516165.2198±78.10.3985.6~49560.878.0
Cu164±79.00.4817.9~3952346.3166±77.50.4723.2~67023.148.2
Hg0.11±0.161.360.02~4.740.0650.0580.12±0.141.090.02~1.210.0440.076
Ni77.2±16.90.2224.4~1752742.581.5±17.00.2134.1~15828.651.0
Pb38.3±57.41.5015.3~20332640.627.3±11.80.439.46~75.924.740.2
Zn167±65.50.3950.2~20597489.7141±33.00.2369.7~27371.199.1
pH值5.67±0.680.124.44~8.026.75.75.73±0.640.114.53~7.52\\
), ArticleFig(id=1241057223930082030, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=表2, caption=

研究区土壤重金属含量统计(mg/kg)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素表层土壤(n=1487)深层土壤(n=374)
均值±标准差变化系数范围中国土壤背景值云南背景值均值±标准差变化系数范围中国土壤背景值云南背景值
As18.8±23.11.232.03~33811.218.418.0±21.51.191.38~25011.525.4
Cd1.81±0.970.540.48~11.10.0970.2180.67±1.342.020.08~13.60.0840.155
Cr196±84.70.4348.9~5516165.2198±78.10.3985.6~49560.878.0
Cu164±79.00.4817.9~3952346.3166±77.50.4723.2~67023.148.2
Hg0.11±0.161.360.02~4.740.0650.0580.12±0.141.090.02~1.210.0440.076
Ni77.2±16.90.2224.4~1752742.581.5±17.00.2134.1~15828.651.0
Pb38.3±57.41.5015.3~20332640.627.3±11.80.439.46~75.924.740.2
Zn167±65.50.3950.2~20597489.7141±33.00.2369.7~27371.199.1
pH值5.67±0.680.124.44~8.026.75.75.73±0.640.114.53~7.52\\
), ArticleFig(id=1241057224135602940, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Table 3, caption=

Statistical classification of heavy metal Igeo in topsoil

, figureFileSmall=null, figureFileBig=null, tableContent=
污染分级AsCdCrCuHgNiPbZn
样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)
无污染115877.8700664.4421414.3976951.7126217.62143196.2323615.87
轻度污染26517.82161.0880153.8738125.6251934.90121081.37473.16123282.85
偏中度污染523.5046431.2058239.1477151.8516611.16151.0150.34161.08
中度污染80.5481154.54382.561218.14261.750020.1320.13
偏重度污染40.2717912.04000050.340010.0710.07
重度污染00161.08000010.07000000
严重污染0010.07000010.070010.0700
), ArticleFig(id=1241057225704272656, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=表3, caption=

土壤重金属地累积指数分级统计

, figureFileSmall=null, figureFileBig=null, tableContent=
污染分级AsCdCrCuHgNiPbZn
样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)样数占比(%)
无污染115877.8700664.4421414.3976951.7126217.62143196.2323615.87
轻度污染26517.82161.0880153.8738125.6251934.90121081.37473.16123282.85
偏中度污染523.5046431.2058239.1477151.8516611.16151.0150.34161.08
中度污染80.5481154.54382.561218.14261.750020.1320.13
偏重度污染40.2717912.04000050.340010.0710.07
重度污染00161.08000010.07000000
严重污染0010.07000010.070010.0700
), ArticleFig(id=1241057225838490399, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=EN, label=Table 4, caption=

Rotated component matrix of the topsoil

, figureFileSmall=null, figureFileBig=null, tableContent=
指标F1F2F3F4F5F6F7
As-0.50*-0.48*-0.040.32*0.280.060.17
Cd-0.13-0.170.40*0.41*0.40*0.130.28
Cr-0.210.29-0.120.020.83*-0.01-0.10
Cu0.92*-0.190.070.06-0.05-0.10-0.02
Hg-0.22-0.42*0.180.040.43*0.070.33*
N0.14-0.140.91*0.02-0.05-0.080.07
Ni0.320.01-0.050.110.87*-0.020.04
P0.77*-0.010.44*0.01-0.13-0.050.00
Pb-0.08-0.040.000.96*-0.050.00-0.09
Zn0.17-0.080.140.94*0.170.000.05
SiO2-0.88*0.29-0.03-0.03-0.12-0.010.17
Ti0.95*-0.030.04-0.03-0.02-0.11-0.08
Al2O30.45*-0.69*-0.040.060.15-0.04-0.24
TFe2O30.95*-0.160.010.010.06-0.10-0.09
MgO-0.130.90*-0.14-0.040.130.140.08
CaO-0.080.38*-0.010.05-0.020.78*0.17
Na2O0.050.86*-0.14-0.060.260.030.06
K2O-0.47*0.65*-0.19-0.04-0.110.080.01
Corg0.17-0.090.90*0.12-0.040.03-0.03
pH值-0.220.07-0.220.090.010.78*0.12
WIG-0.39*0.69*-0.12-0.02-0.060.47*0.13
Clay0.22-0.44*-0.130.07-0.140.12-0.39*
Light0.02-0.090.14-0.070.020.58*-0.18
Slope-0.170.040.17-0.01-0.03-0.080.76*
Height-0.04-0.220.26-0.02-0.01-0.22-0.57*
), ArticleFig(id=1241057225989485362, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057213230412495, language=CN, label=表4, caption=

表层土壤主成分分析旋转成分矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
指标F1F2F3F4F5F6F7
As-0.50*-0.48*-0.040.32*0.280.060.17
Cd-0.13-0.170.40*0.41*0.40*0.130.28
Cr-0.210.29-0.120.020.83*-0.01-0.10
Cu0.92*-0.190.070.06-0.05-0.10-0.02
Hg-0.22-0.42*0.180.040.43*0.070.33*
N0.14-0.140.91*0.02-0.05-0.080.07
Ni0.320.01-0.050.110.87*-0.020.04
P0.77*-0.010.44*0.01-0.13-0.050.00
Pb-0.08-0.040.000.96*-0.050.00-0.09
Zn0.17-0.080.140.94*0.170.000.05
SiO2-0.88*0.29-0.03-0.03-0.12-0.010.17
Ti0.95*-0.030.04-0.03-0.02-0.11-0.08
Al2O30.45*-0.69*-0.040.060.15-0.04-0.24
TFe2O30.95*-0.160.010.010.06-0.10-0.09
MgO-0.130.90*-0.14-0.040.130.140.08
CaO-0.080.38*-0.010.05-0.020.78*0.17
Na2O0.050.86*-0.14-0.060.260.030.06
K2O-0.47*0.65*-0.19-0.04-0.110.080.01
Corg0.17-0.090.90*0.12-0.040.03-0.03
pH值-0.220.07-0.220.090.010.78*0.12
WIG-0.39*0.69*-0.12-0.02-0.060.47*0.13
Clay0.22-0.44*-0.130.07-0.140.12-0.39*
Light0.02-0.090.14-0.070.020.58*-0.18
Slope-0.170.040.17-0.01-0.03-0.080.76*
Height-0.04-0.220.26-0.02-0.01-0.22-0.57*
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宣威地区土壤重金属潜在污染风险评价及影响因素解析
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韩伟 1, 2, 3 , 宋云涛 1, 2, 3 , 郭志娟 1, 2, 3, * , 曾道明 1, 2, 3 , 贺灵 1, 2, 3 , 成晓梦 1, 2, 3 , 孙彬彬 1, 2, 3, 4 , 张富贵 1, 3 , 张利 1, 3
中国环境科学 | 土壤污染与控制 2025,45(5): 2643-2653
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中国环境科学 | 土壤污染与控制 2025, 45(5): 2643-2653
宣威地区土壤重金属潜在污染风险评价及影响因素解析
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韩伟1, 2, 3 , 宋云涛1, 2, 3, 郭志娟1, 2, 3, * , 曾道明1, 2, 3, 贺灵1, 2, 3, 成晓梦1, 2, 3, 孙彬彬1, 2, 3, 4, 张富贵1, 3, 张利1, 3
作者信息
  • 1.中国地质科学院地球物理地球化学勘查研究所,河北 廊坊 065000
  • 2.自然资源部地球化学探测重点实验室,河北 廊坊 065000
  • 3.中国地质调查局土地质量地球化学调查评价研究中心,河北 廊坊 065000
  • 4.联合国教科文组织全球尺度地球化学国际研究中心,河北 廊坊 065000
  • 韩伟(1985-),男,河北保定人,高级工程师,硕士,主要研究方向为环境地球化学和勘查地球化学.发表论文27篇..

通讯作者:

* 责任作者,高级工程师,
Evaluation and analysis influencing factors of potential heavy metal pollution risk in soil of Xuanwei City
Wei HAN1, 2, 3 , Yun-tao SONG1, 2, 3, Zhi-juan GUO1, 2, 3, * , Dao-ming ZENG1, 2, 3, Ling HE1, 2, 3, Xiao-meng CHENG1, 2, 3, Bin-bin SUN1, 2, 3, 4, Fu-gui ZHANG1, 3, Li ZHANG1, 3
Affiliations
  • 1.Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Science, Langfang 065000, China
  • 2.Key Laboratory of Geochemical Exploration, Ministry of Natural Resources, Langfang 065000, China
  • 3.Geochemical Research Center of Soil Quality, China Geological Survey, Langfang 065000, China
  • 4.UNESCO International Center on Global-scale Geochemistry, Langfang 065000, China
出版时间: 2025-05-20
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我国西南生态功能保护区内存在土壤重金属高含量区,为探究其潜在污染风险及影响因素,选择云南省宣威地区土壤为研究对象,结合地理、地质、人类活动等相关资料,对区内表层组合土壤样品1487份、深层组合土壤样品374份中的8种重金属元素含量特征进行了分析,分别利用地累积指数法和潜在生态危害指数法评价了表层组合土壤的潜在污染风险,采用主成分分析法和地理探测器对其影响因素进行了解析.结果显示,相对于中国土壤A层、C层背景值研究区表、深层土壤中重金属均显示富集;相对于云南省A层、C层土壤背景值大部分重金属亦显示富集;Cd、Hg、Pb存在较高的潜在污染风险,Cu、Cr、Ni、Zn、As则潜在污染风险较低;地质背景、黏土矿物、有机质、矿业活动、地形地貌是土壤中重金属元素的主要影响因素,多影响因素的协同作用可能会使重金属富集加剧,pH值、CaO、Light(灯光指数)、WIG对重金属富集的影响则较小.

宣威地区  /  土壤重金属  /  潜在生态危害指数  /  地累积指数  /  主成分分析

High-concentration areas of soil heavy metals exist in ecological functional protection zones of Southwest China. To investigate their potential pollution risks and influencing factors, this study selected soils in the Xuanwei region of Yunnan Province as the research subject. Combining geographical, geological, and anthropogenic activity data, the content characteristics of eight heavy metal elements were analyzed in 1487 surface soil samples and 374 deep soil samples. The geo-accumulation index and potential ecological risk index were used to assess the potential pollution risks of surface soils, while principal component analysis(PCA)and geographical detector methods were employed to identify influencing factors. The results revealed that heavy metals in both surface and deep soils were enriched compared to the A-layer and C-layer background values of Chinese soils. Most heavy metals also exhibited enrichment relative to the A-layer and C-layer background values of Yunnan Province. Cd, Hg, and Pb posed relatively high potential pollution risks, whereas Cu, Cr, Ni, Zn, and As showed lower risks. The main influencing factors for heavy metal enrichment included geological background, clay minerals, organic matter, mining activities, and topography. Synergistic effects of multiple factors could exacerbate heavy metal enrichment, while pH, CaO, Light(light index), and WIG exhibited minimal impacts.

Xuanwei  /  soil heavy metals  /  potential ecological risk index  /  geo-accumulation index  /  principal component analysis
韩伟, 宋云涛, 郭志娟, 曾道明, 贺灵, 成晓梦, 孙彬彬, 张富贵, 张利. 宣威地区土壤重金属潜在污染风险评价及影响因素解析. 中国环境科学, 2025 , 45 (5) : 2643 -2653 .
Wei HAN, Yun-tao SONG, Zhi-juan GUO, Dao-ming ZENG, Ling HE, Xiao-meng CHENG, Bin-bin SUN, Fu-gui ZHANG, Li ZHANG. Evaluation and analysis influencing factors of potential heavy metal pollution risk in soil of Xuanwei City[J]. China Environmental Science, 2025 , 45 (5) : 2643 -2653 .
宣威地区属于我国珠江源生态功能保护区和西南喀斯特生态功能保护区,是确保国家生态安全方面具有重要作用的区域.近年来,我国开展的多目标区域地球化学调查发现,在西南生态功能区存在着一个规模巨大重金属地质高背景区域[1-3].由于我国西南地区遍布的碳酸盐岩在自然风化成壤过程中重金属次生富集是造成土壤重金属高含量的主要原因[4-6],该区的重金属风险评价一直是学者们的研究热点.赵东杰等[7]认为河漫滩沉积物中重金属含量主要受地质背景影响;王雪雯等[8]通过研究不同土地利用方式下的重金属分布特征,认为黔西北地区大部分重金属污染是受地质高背景和人类活动共同作用的结果;王乔林等[9]认为滇西土壤中Cr、Cu和Ni等重金属含量主要受成土母岩的控制;韩伟等[10]在研究昭通市峨眉山玄武岩区土壤中重金属含量特征时,认为土壤中重金属Cu主要来源于峨眉山玄武岩成土母质,而其他重金属元素影响因素较为复杂;基于乡镇尺度研究显示,在宣威市热水镇农田中土壤中重金属含量远超云南省土壤背景值,潜在生态风险较高[11],地质背景亦被认为是其成因的重要原因之一;而洪涛等[12]通过研究云南东南部峰丛洼地地区土壤重金属的污染特征及生态风险状况,则认为Cd、Cr、Ni主要来源为化石燃料燃烧,Pb、Zn为交通运输,Cu为自然来源,Hg为农业生产;还有研究认为土壤酸碱度也是影响土壤中重金属元素含量的重要因素之一[13].由此可知,土壤重金属的地球化学分布特征和迁移转运过程受到成土母质、人类活动、自然环境等多因素的潜在控制,难以普适性的结论阐明这类地质高背景区土壤重金属元素的地球化学行为、生态风险及影响机制.以元素表生地球化学特征为基础,利用经典潜在生态风险评价模型和多元统计方法,深入研究该类地区土壤重金属元素地球化学特征、潜在生态风险等具有重要意义[14].本文利用宣威地区土壤元素分析数据,结合区内土壤理化性质、人类活动自然环境等资料,以重金属元素为重点,充分研究土壤中重金属元素含量特征,运用典型模型对其开展潜在风险评价,并采用主成分分析法对重金属影响因素进行探讨,详细刻画出宣威地区土壤重金属污染状况及其影响因素,以期为我国西南生态功能保护区的重金属生态风险评估与管护提供科学参考.
图1所示,宣威地区地处云南高原东北部,为云南高原向贵州高原过渡的斜坡地带.地势西北高、东南低,海拔920~2868m,西部和中北部的乌蒙山的中列山系具有较齐的山峰线和较平缓的山顶面,地形坡度在15°~25°之间,东部的乌蒙山东列山系属中切割山地,山体大部分由碳酸盐岩构成,下部陡峭,坡度30°~35°.境内河流以老官营梁子、分水岭、公鸡山岭脊为界,分属长江水系和珠江水系.主干流有西南的小江属长江水系,东北的可渡河及东南的革香河属珠江水系.该区属低纬高原季风气候,冬春干旱,夏秋降水集中,年变率大,年平均13.4℃,最高年平均温14.6℃,最低年平均温12.7℃;多年平均日照2018.5h,日照百分率为47%.土壤类型主要为红壤、紫色土、黄壤、黄棕壤、水稻土、新积土、粗骨土、石灰(岩)土.其中面积最大的为红壤,占总面积的68.13%;石灰(岩)土面积最小,仅占0.61%.土地利用类型主要为林地、耕地、草地、裸地、城镇村及工矿用地,面积比例分别为47.08%、44.40%、3.82%、2.61%、1.62%,其他用地类型较少.区内岩石类型较为复杂,内源沉积岩主要以灰岩、白云岩为主,火山岩主要为峨眉山玄武岩,碎屑沉积岩主要为砂岩、泥岩及页岩,第四系则主要为不同时期、不同成因类型的松散堆积物,其中部分沉积碎屑岩与内源沉积岩为互层,玄武岩产于下二叠统茅口组灰岩之上,被上二叠统宣威组的砂泥岩整合覆盖[15].区内主要矿产类型有煤、锰、铜、锌等,但除煤、锰外,其他金属矿规模均较小.
本研究覆盖整个宣威地区,样品采集点位采用网格布设采[16],表层土壤网格间距为1km×1km,采集深度为0~20cm,样品密度为1点/km2;深层土壤网格间距为2km×2km,采集深度为120~150cm,采样方式为深层土壤取样器取样,样品密度为1点/4km2.结合土地利用现状调查资料,主要采集于较大面积旱地中,于布设点中心周围3处采集,采集重量为1kg,并记录采样地块农作物、土壤质地、侵蚀、地貌类型等信息.采集后置于避光处阴干,阴干后过0.85mm孔径尼龙筛,按表层2km×2km、深层4km×4km网格进行样品组合,各个样品均混合均匀后取同等重量进行组合.
本研究共取得表层组合样品1487份、深层组合样品374份,测试指标为As、Cd、Cr、Cu、Hg、Pb、Ni、Zn、pH值、N(全氮)、P(全磷)、K2O、SiO2、Al2O3、TFe2O3(全铁)、MgO、CaO、Na2O、Corg(有机碳)、Ti.所有样品分析测试均由中国地质科学院地球物理地球化学勘查研究所实验测试中心和四川省地质矿产勘查开发局成都综合岩矿测试中心联合完成.样品分析测试依据主要为《多目标区域地球化学调查规范(1:250000)》(DZ/T 0258-2014)[16],验收合格的土壤样品经混匀后,过20目筛取20g样品装瓶用作pH值分析,另取100g样品在60℃以下的烘箱中烘干后用无污染的行星球磨机粉碎至200目粒度,分装4份,每份5g.其中pH值采用点位法[18]测定,As采用氢化物-原子荧光光谱法,Hg采用冷蒸气-原子荧光光谱法,Al2O3、K2O、TFe2O3、CaO、Na2O、SiO2、Ti、P采用X射线荧光光谱法,Corg采用高频燃烧-红外碳硫仪测定,N采用氧化燃烧-气相色谱法,其他元素均采用等离子体质谱法测定.样品分析过程中采用国家一级标准物质进行准确度控制,在每500个样品中密码滚动插入12个土壤标准物质与样品同条件进行分析,每种元素的每次分析结果单独计算单个标准物质测量值与标准值对数差,要求其不大于0.12;精确度控制采用每50个样品中插入4个土壤国家一级标准物质,按每个标准物质计算测定值与标准值的对数偏差并计算4个监控样的对数标准偏差,要求其不大于0.17.本研究的分析测试工作方法、重复分析质量、分析准确度及精确度均等于或优于文献[16],样品分析结果合格率为100%.
目前被学者广泛应用的土壤重金属风险评价方法主要为地累积指数法[17]、潜在生态危害指数法[18]、富集因子法[19]、内梅罗综合污染指数法[20-21]等,由于本次研究区地质背景较为复杂,岩石类型较多,为减小地质背景差异引起的背景值的变动,地累积指数法较为适合本研究区表层土壤重金属污染程度评价,而潜在生态危害指数法引入了毒性响应系数,能够将重金属的环境生态效应与毒理学联系起来,使评价结果不仅可以为土壤环境质量提供依据,还能为人们的身体健康提供科学参考[22],故本次研究选取地累积指数法和潜在生态危害指数法对研究区表层土壤重金属潜在风险进行评价.运用SPSS 25及python对表层和深层土壤元素含量数据进行数理统计、主成分分析等研究,利用Excel 2016计算地累积指数及潜在生态危害指数,ArcGIS 10.8.1绘制了生态风险等级空间分布,并采用CorelDRAW 2021对图件进行了矢量化.
地累积指数由Muller于20世纪60年代提出,是一种定量评价重金属污染的分析方法.其计算公式为:
式中:Igeo为元素i地累积指数;Ci表示重金属元素i在表层土壤中的含量,mg/kg;Bi表示重金属元素i的参考背景值,本次研究采用云南省A层土壤背景值,mg/kg;k为考虑地质背景不同引起的背景值变动而取的修正系数,本次研究k取值为1.5.
评价结果分为无污染(Igeo≤0)、轻度污染(0<Igeo≤1)、偏中度污染(1<Igeo≤2)、中度污染(2<Igeo≤3)、偏重度污染(3<Igeo≤4)、重度污染(4<Igeo≤5)和严重污染(Igeo>5)7个等级.
瑞典科学家Hakanson在1980年提出了潜在生态危害指数(RI).计算公式如下:
式中:RI为采样点多种重金属综合潜在生态危害指数,i代表某类重金属元素,m代表重金属的种类数;Ei为某单个重金属的潜在生态危害指数;Ti为对应重金属的毒性响应系数[23](As=10、Zn=1、Ni=5、Cu=5、Hg=40、Pb=5、Cr=2、Cd=30);Ci为该元素的实测含量,mg/kg;Bi为该元素的评价标准含量,本次研究采用云南省A层土壤背景值,mg/kg.
考虑到该评价结果的精度和普适性,本研究采用Jiang等[24]对分级标准的调整方法,将Ei和RI结果分级如表1所示.
对研究区内表、深层样品重金属元素的分析数据进行了统计(表2),并结合土地利用类型对重金属元素的含量和富集特征进行了探讨.研究区表层土壤酸碱度均值为5.67±0.68,低于中国土壤A层背景值,与云南土壤背景值较为相当,86.82%的样品属于酸性土壤(pH<6.5),12.04%的样品呈中性(6.5≤pH<7.5),仅1.14%的样品呈碱性.表层土壤中As含量为2.03~338mg/kg,Cd为0.48~11.1mg/kg,Cr为48.9~551mg/kg,Cu为17.9~395mg/kg,Hg为0.02~4.74mg/kg,Ni为24.4~175mg/kg,Pb为15.3~2033mg/kg,Zn为50.2~2059mg/kg,且平均含量不同程度高于中国土壤A层背景值,各重金属元素均显示富集(富集系数大于1),其中Cd、Cu、Cr、Ni、Zn富集系数均大于2,分别为18.6、7.15、3.21、2.86、2.26;相对云南省背景值,Cd、Cu、Cr显示出较为富集,其富集系数分别为8.28、3.55、3.00,仅Pb显示亏损(富集系数小于1).从变化系数看,除Ni外,其余元素变化系数均超过了30%,表明其空间的离散和变异程度较高[26].如图2所示,不同土地利用类型土壤中,As、Cd、Cr、Hg含量在裸地中含量较高,其均值分别为36.8,2.54,248,0.18mg/g,与中国土壤A层背景值比较,其富集系数均大于2,Cd的富集系数甚至达到26.2;Cu则在林地中含量较高,均值为173mg/g,其富集系数为7.53;Ni、Zn和Pb则在各土地利用类型土壤中含量相差较小,虽其富集系数亦相差不大,但亦均显示较为富集.
有研究表明深层土壤受到人类活动影响较小[27],能够在一定程度上反映区域地质背景.研究区深层土壤酸碱度略高于表层土壤,均值为5.73±0.64,其中84.49%的样品显示酸性土壤,15.24%的样品显示中性土壤,碱性土壤样品最少,仅占0.27%.深层土壤中重金属As含量为1.38~250mg/kg,Cd为0.08~13.6mg/kg,Cr为85.6~495mg/kg,Cu为23.2~670mg/kg,Hg为0.02~1.21mg/kg,Pb为9.46~75.9mg/kg,Zn为69.7~273mg/kg,相较于中国土壤C层背景值,其均值亦表现出富集,富集系数大于2的元素分别为Cd、Cu、Cr、Ni、Hg;对比云南省C层土壤背景值,依然是Cd、Cu、Cr富集较高,显示亏损的元素为As和Zn,其富集系数分别为0.71和0.68.仅Ni和Zn变化系数较小,其余元素变化系数亦超出了30%,表明深层土壤中重金属空间分异性较大,但相比表层土壤略有减小.
由此可见,研究区内重金属元素相对中国土壤背景值和云南省土壤背景值较为富集,且区域地质背景亦较高,这与前人的研究结果一致[1-3],故区内可能存在不同程度的重金属潜在风险.
根据地累积指数法和潜在生态危害指数法,分别对研究区表层土壤进行了污染风险评价.
地累积指数评价结果如表3所示,As元素污染分级主要集中于无污染和轻度污染,虽然其总占比高达95.7%,且未出现重度及严重污染等级,但显示有4个样点为偏重度污染;Cd元素污染分级以偏中度污染、中度污染、偏重度污染为主,其占比为97.78%,不仅无无污染分级,甚至出现了重度污染样品数16件和严重污染样品1件;Cr、Cu元素污染分级情况较为一致,污染分级均在中度污染以上,未出现偏重度污染以下等级,且分级集中在轻度污染及偏中度污染;Hg元素虽然表现出高达97.78%的样品属于偏中度污染以上等级,但是其显示有5件样品属偏重度污染,重度污染和严重污染等级样品各1件;Ni元素污染等级较为良好,主要为轻度污染和无污染等级,占比为98.99%,且无中度污染等级以下样品;Pb元素污染分级以无污染为主,占比高达96.23%,值得注意的是其显示出1件样品为严重污染;Zn元素污染分级主要为无污染和轻度污染,占比为98.72%,且未显示重度和严重污染等级.根据地累积指数法评价结果可以看出,Cd、Hg、Pb、As污染程度较高,需引起一定重视.
为详细研究各重金属潜在生态危害指数评价结果,统计了各分级所占百分比(图3),以2km×2km网格代表每个分析点的土壤重金属潜在生态危害指数分级,绘制了其空间分布图(图4),As元素主要为轻微危害等级,占比为98.39%,其次为中等危害等级,占1.28%,主要分布于研究区西南及东南部,较高和高危害等级点位分别仅有3个和2个,分布于研究区南部、中部和东部边缘,无很高危害等级;Pb元素显示轻微危害等级占99.87%,无中等和很高危害等级,较高和高危害等级各仅有1点,各占比仅为0.07%,分布于中东部区域;Cd元素则未显示轻微危害等级,中等危害等级占0.47%,分布于研究区东南部,较高等级占21.45%,主要分布于西北部、南部和东南部,高危害等级占比最高,达59.85%,广泛分布于研究区内,很高危害等级占比18.22%,主要分布于中部、北部和东部,表明该元素潜在生态危害较高;Hg元素轻微等级占比为22.73%,主要分布于中北部和中南部,中等占比最高,为46.67%,广泛分布于研究区内,较高等级占比为24.4%,主要分布于中东部和中西部,高危害等级占比为5.31%,主要分布于中部和东部边境地区,很高危害等级占比为1.14%,主要分布于宣威市城区附近;Cr、Ni和Zn元素显示潜在生态危害较低,其危害等级均为轻微;Cu与Cr类似,轻微危害等级占99.87%,仅有2点位显示中等危害等级,分布于宣威市城区西部.由此可知,研究区主要潜在生态危害重金属元素为Cd、Hg、As、Pb,与地累积指数得出的评价结果较为一致.
综合潜在生态危害指数(RI)是各个重金属潜在生态危害指数的和,能够综合反映该采样单位的重金属潜在生态危害.由图3图4可知,研究区无轻微危害等级,中等危害等级占比5.78%,主要分布于北部和东南部,较高危害等级占比最高,为63.21%,在研究区内广泛分布,高危害等级占比27.64%,在研究区内呈西南-东北向长条状分布,很高危害等级占比3.36%,主要分布于宣威市城区周边及东北部边境地区,表明研究区内存在一定程度的重金属潜在生态危害.
综上可知,研究区内土壤潜在生态风险较高的重金属元素主要为Cd、Hg、As、Pb,而Cu、Cr、Ni、Zn潜在生态风险较低;Cd潜在生态高风险呈大片面状分布,Hg则呈单点状及小片面状分布,其余元素则主要为点状分布.
在环境科学中主成分分析(PCA)常被用来分析和识别环境样本中的主要污染源及影响因素[28-30],地理探测器主要被用来分析各种现象的驱动力和影响因子以及多因子交互作用[31],其结果中的q值从而能够定量化、空间化分析多种因素的影响效应在母岩风化过程中,Ca、Mg元素大量淋失所导致的体积和质量的巨大损失,造成了风化土壤重金属相对富集[32].有学者认为相对高程、坡度与土壤中有机质和全氮含量具有显著的相关性[33].为探究宣威地区表层土壤重金属来源及影响因素,本次研究还引入了土壤中N(全氮)、P(全磷)、K2O、SiO2、Al2O3、TFe2O3、MgO、CaO、Na2O、Corg(有机碳)、Ti、pH值、WIG(风化指数)[34]、Clay(黏土量)[35]、Light(灯光指数,用来间接反映人类生活活动影响)[36]、Slope(坡度)及Height(高度)[37],与研究区表层土壤中重金属元素同时进行主成分和地理探测器分析,经KMO和Bartlett检验,得到KMO值为0.739,Bartlett球形度检验显著性P=0.00,表明变量数据间存在足够的相关性,适合进行主成分分析,提取特征值大于1的主成分,前7个公共因子解释的累计方差高达77.37%,足以解释原始变量变异性的程度.分析其旋转后成分矩阵(表4),其中重金属元素As、Cd、Hg、Ni在多个主成分中载荷均较高,表明其可能具有多源成因.
第一主成分其载荷较高的重金属元素有Cu、As和Ni,并伴有TFe2O3、P、SiO2、Ti、K2O、Al2O3、WIG的高载荷,其初始特征根方差百分比高达28.35%.在元素地球化学研究中认为SiO2、K2O、Al2O3属于造岩元素[38],代表地质背景.有学者测试了云南省昭通地区89件新鲜峨眉山玄武岩中元素含量,显示出高含量Cu和Ti是峨眉山玄武岩典型特征之一[39],而风化作用导致峨眉山玄武岩顶部风化壳富集Fe、Al等元素,并形成了一套Fe-Al岩系[40].可以判断峨眉山玄武岩为第一主成分的主要来源,该类地质背景影响了土壤中元素含量及组合.第二主成分初始特征根方差百分比为13.57%,载荷较高元素为As、Hg、Al2O3、MgO、CaO、Na2O、K2O、WIG、Clay,可以看出该主成分中除重金属元素外,造岩元素亦较多,且伴有黏土含量指标及风化指数.在我国南方地区成土母质风化成土过程中,由于湿热多雨的气候导致土壤中造岩元素中较为活泼的元素大量流失,如K、Na、Mg、Ca,而Fe、Al氧化物则逐渐聚集,即富铝化过程,使土壤中含大量黏土[41],有研究表明铁氧化物和黏土矿物等都对Hg2+和As具有一定的吸附作用,可形成结合态汞及固定态砷[42-43].故第二主成分可以解释为As、Hg元素受成土过程中黏土矿物的影响.Cd、N、P、Corg为第三主成分主要载荷元素,初始特征根方差百分比为10.37%.有机质泛指土壤中以各种形式存在的含碳有机化合物,是植物所需的氮、磷、微量元素等各种养分的主要来源,表明该主成分可能为有机质对重金属Cd含量的影响.已有研究证实,有机质中的腐殖质属于一类高分子有机化合物,不仅含有多种含氧功能团,如羧基、酚羟基等,容易和重金属元素发生络合或鳌合反应,而且其大部分以有机颗粒或有机膜被覆的形式与土壤中的黏土矿物、氧化物等无机颗粒相结合形成有机、无机复合胶体,增加了土壤的表面积和表面活性,使得土壤对重金属的吸附能力增加[44];天然有机质的主要成分腐殖酸(HAs)对土壤重金属的迁移转化和生物有效性具有重要影响,高分子量的胡敏酸(HA)可提高土壤重金属的固持能力,抑制土壤重金属的植物有效性,而分子量更低的富里酸(FA)作用则相反[45].第四主成分高载荷元素为Cd、Pb、Zn,该组元素均为重金属元素,同时为与矿产资源相关的元素.周艳等人在研究西南某铅锌矿区周边农田土壤中重金属时,多元统计分析结果显示As、Cd、Hg、Pb、Zn来源相似,认为来源于矿山开采和工业活动[46].我国西南地区早在17世纪就有土法炼锌的报道,由于当时工业水平较差,冶炼过程中不仅对Zn元素回收率较低,对其伴生元素未回收利用,并且产生了大量的烟尘和残渣遗留在地表,导致区域内冶炼废渣、土壤、水体中Zn、Pb、Cd含量均很高,通过X射线粉晶衍射技术发现土壤中含有黄铁矿、闪锌矿和方铅矿等硫化物矿物,偶见少量的雄黄和辰砂[14,47];土法炼锌企业于20世纪80年代开始在宣威发展,在2004年全面取缔土法炼锌企业后,宣威市境内遗留下大量锌废渣且无序堆存,对生态环境、土壤、河流及水源造成不同程度污染,并于2015年开展废渣处置工作[48];Cd和Zn有着近似的地球化学性质,但Cd比Zn具有更强的亲硫性,通常Cd会以类质同象置换其他离子而存于闪锌矿中[49],而其很强的主极化能力容易被土壤的胶体溶液强烈吸附而残留原地.因此导致研究区表层土壤中该类元素关系密切,第四主成分指示为工矿业人为活动影响因子.第五主成分载荷较高的为Cr、Ni、Hg、Cd,其初始特征根方差百分比为6.85%.已有很多学者关于碳酸盐岩区土壤中重金属富集进行了研究,王秋艳等[32]根据质量平衡理论认为碳酸盐岩在风化过程中大量Ca、Mg等元素淋失,导致了体积和质量的较大损失,释放的各种重金属以多种形式滞留于土壤中,会致使重金属富集程度增加.另有研究表明认为土壤中Cr、Ni主要以比较稳定的残渣态存在,主要继承于成土母岩[11,50-51],且受人为影响较小[46],研究区的潜在风险评价结果亦显示Cr、Ni潜在污染风险较小.由此可以认为该主成分为研究区内碳酸盐岩地质背景对土壤中重金属富集的影响.
与其他主成分不同,第六主成分载荷较高的指标为pH值、CaO、Light(灯光指数)、WIG,重金属元素载荷系数均较小,其初始特征根方差百分比仅5.58%.表明该4类因素对土壤中重金属元素影响复杂或影响较小.第七主成分初始特征根方差百分比仅为4.24%,载荷较高的指标有Slope(坡度)、Height(高度)、Clay和Hg. Hg是在常温常压下唯一以液态存在的金属,常温下会蒸发出汞蒸气,并在空气中存在状态较为稳定,就使得Hg易于随大气沉降迁移.有研究证实高山森林土壤汞存在明显的海拔分布格局[52],在较高海拔的山地环境可能具有放大效应,高山地区表层土壤和植被是大气汞沉降的重要有效载体,山地地形因素对汞的“拦截效应”有较大影响[53],而研究区内多为较高海拔的山地,地势起伏不平,山地上植被亦覆盖较厚,故该主成分表征为山地地形对重金属元素的影响因子.
地理探测器分析表明,影响As元素在土壤中含量的主要因素为Ti(q=0.21)>P(q=0.16)>Na2O(q=0.15)>TFe2O3q=0.14),其余因素q值均小于0.1;Cd元素的主要影响因素为Corg(q=0.09)>N(q=0.08)>K2O(q=0.06)>Clay(q=0.06)>MgO(q=0.05),且其任意2因素间均为协同加强,主控因素为有机质;Cr元素的主要影响因素为TFe2O3q=0.32)>Ti(q=0.30)>P(q=0.25),Cu元素的主要影响因素为TFe2O3q=0.82)>Ti(q=0.80)>SiO2q=0.70)>P(q=0.58)>WIG(q=0.40),这与主成分分析的第一主成分结果较为一致,Hg元素的主要影响因素为Clay(q=0.06)>Na2O(q=0.05)>MgO(q=0.0.04),这与主成分分析的第七主成分结果较为一致,其主受控因素为黏土矿物;影响Ni元素的因素q大于0.1的为TFe2O3q=0.27)>SiO2q=0.18)>P(q=0.10),影响Pb元素的因素q值均较小,大于0.01的仅为Na2O(q=0.02)>MgO(q=0.01)>WIG(q=0.01),影响Zn元素的各因素q值亦较小,大于0.05的仅为Corg(q=0.05)>SiO2q=0.05),可能所选各因素均不是Pb、Zn元素的主控因素.
综上所述,研究区内地质背景、黏土矿物、有机质、矿业活动、地形地貌均能影响土壤中重金属元素,且部分重金属元素受到多种因素影响.其中Cd元素受三种因素影响,即有机质、矿业活动和碳酸盐岩,且其载荷值相差很小,可以认为是三种影响因素协同作用造成该重金属元素在研究区富集,Corg可认为是主控因素,故形成较高的潜在风险;Hg则主要受黏土矿物、碳酸盐岩地质背景及地形地貌影响,但由于地形地貌因素载荷值相对较小,故其影响强度要弱于前两种因素;As主要受峨眉山玄武岩地质背景、黏土矿物和矿业活动影响,根据载荷值和地理探测器分析结果可以看出地质背景因素大于其他影响因子;Cu、Cr、Ni主要受不同地质背景影响,受其他因素影响均较小;Pb、Zn高载荷值主要出现于矿业活动主成分,其他主成分中载荷值均很小,且其地理探测器分析结果各因素q值均较小,表明其受影响因素较为单一.
3.1 研究区表层、深层土壤中重金属均值相对于中国土壤A层、C层背景值均显示富集,Cd、Cu、Cr、Ni等富集系数较高;表层土壤相对于云南省A层背景值除Pb显示亏损外,其余重金属元素均显示富集,深层土壤相对于云南省C层背景值Cd、Cu、Cr富集系数较高,As和Zn则显示亏损.
3.2 通过地累积指数法和潜在生态危害指数法对研究区表层土壤进行潜在污染风险评价,评价结果较为一致,综合评价结果认为Cd、Hg、As、Pb存在较高潜在污染风险,而Cu、Cr、Ni、Zn潜在污染风险较低.
3.3 研究区内重金属元素主成分和地理探测器分析结果显示地质背景、黏土矿物、有机质、矿业活动、地形地貌是土壤中重金属元素的主要影响因素,且不同重金属元素主要受控因素种类不尽相同,潜在污染风险较高的重金属元素受到的影响因素较为复杂,潜在污染风险较低的多数重金属元素受到影响因素较为单一,可能多影响因素的协同作用使重金属富集加剧;pH值、CaO、Light(灯光指数)、WIG对重金属富集的影响则较小.
  • 第二次青藏高原综合科学考察研究(2019QZKK020404)
  • 乌蒙山区土地质量地球化学调查(DD20190522)
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2025年第45卷第5期
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  • 接收时间:2024-09-04
  • 首发时间:2026-03-18
  • 出版时间:2025-05-20
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  • 收稿日期:2024-09-04
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第二次青藏高原综合科学考察研究(2019QZKK020404)
乌蒙山区土地质量地球化学调查(DD20190522)
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    1.中国地质科学院地球物理地球化学勘查研究所,河北 廊坊 065000
    2.自然资源部地球化学探测重点实验室,河北 廊坊 065000
    3.中国地质调查局土地质量地球化学调查评价研究中心,河北 廊坊 065000
    4.联合国教科文组织全球尺度地球化学国际研究中心,河北 廊坊 065000

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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