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物探与化探  2023, Vol. 47 Issue (1): 1-13    DOI: 10.11720/wtyht.2023.2613
  地质调查·资源勘查 本期目录 | 过刊浏览 | 高级检索 |
调查评价的土壤元素累积趋势预测——以广西南宁市西乡塘区为例
王磊1,2(), 卓小雄1,2, 吴天生2, 凌胜华3, 钟晓宇2, 赵晓孟1,4
1.广西土地质量地球化学评价项目办公室,广西 南宁 530023
2.广西壮族自治区地质调查院,广西 南宁 530023
3.广西壮族自治区三○七核地质大队,广西 贵港 537100
4.广西壮族自治区二七二地质队,广西 南宁 530033
Prediction of the soil element accumulation trends based on 1∶250 000 and 1∶50 000 geochemical surveys and assessments of land quality:A case study of Xixiangtang District, Nanning City, Guangxi zhuang Autonomous Region
WANG Lei1,2(), ZHUO Xiao-Xiong1,2, WU Tian-Sheng2, LING Sheng-Hua3, ZHONG Xiao-Yu2, ZHAO Xiao-Meng1,4
1. Project Office of Land Quality Geochemical Assessment of Guangxi, Nanning 530023, China
2. Guangxi Institute of Geological Survey, Nanning 530023, China
3. No. 307 Nuclear Geological Team of Guangxi Zhuang Autonomous Region, Guigang 537100, China
4. No. 272 Gedogical Team of Guangxi Zhuang Autonomous Region, Nanning 530033, China
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摘要 

土壤重金属元素含量影响土壤环境质量,依据调查数据采用不同模型对土壤重金属元素含量进行预测是研究土壤元素含量及土壤环境质量变化趋势的重要手段。在研究区1∶25万多目标区域地球化学调查和1∶5万土地质量地球化学评价数据基础上,分别采用单时段增量模型和输入输出通量模型预测2027年土壤中5种重金属元素的含量情况,结果显示:两种模型的预测结果有所差异,但变化趋势一致,5种重金属元素含量均有不同程度增加,单时段增量模型的增幅大于输入输出通量模型的增幅;通量模型的各种输入途径中,Cd、Pb主要通过大气干湿沉降进入土壤,As和Cr主要通过施肥进入土壤,Hg主要通过灌溉水进入土壤;对土壤点位的调查数据、预测数据进行土壤环境质量等级划分,优先保护等级的点位数量比例呈现下降趋势,说明土壤环境质量逐年下降。

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王磊
卓小雄
吴天生
凌胜华
钟晓宇
赵晓孟
关键词 土壤重金属地球化学调查累计趋势预测环境质量变化南宁市    
Abstract

The heavy metal element contents in soil affect the quality of soil environment. Their prediction using different models based on survey data is an important means to study the changing trends of soil element contents and soil environmental quality. Based on the data from 1∶250 000 multi-purpose regional geochemical surveys and 1∶50 000 land quality geochemical assessments, this study predicted the contents of five heavy metal elements in the soil of the study area in 2027 using the single-period incremental model and the input-output flux model individually. The results are as follows. The two models yielded different prediction results but consistent trends that the contents of five heavy metal elements increased to different degrees. Moreover, the single-period incremental model yielded larger increments than the input-output flux model. Among the various input channels of the flux model, Cd and Pb entered the soil mainly through dry and wet atmospheric subsidence, As and Cr entered the soil mainly through fertilization, and Hg entered the soil mainly through irrigation water. Based on the survey and prediction data of soil monitoring sites, the soil environmental quality grade was classified for these sites. The proportion of the sites for priority protection showed a downward trend, indicating that the soil environmental quality decreased year by year.

Key wordssoil    heavy metal    geochemical survey    accumulation trend prediction    change in environmental quality    Nanning City
收稿日期: 2021-11-15      修回日期: 2022-04-12      出版日期: 2023-02-20
ZTFLH:  P632  
基金资助:广西重点研发计划专项项目“硒对重金属与生殖健康关系的修正效应——广西壮族辅助生殖队列研究”(桂科AB18050024);国家重点研发计划专项项目“农田地质高背景重金属污染机理研究”(2017YFD0800303);广西壮族自治区自然资源厅项目“广西土壤Se、Ge、Cd等元素异常成因与生态效应研究”(桂国土资函〔2017〕2676号);“西乡塘区土地质量地球化学评价”(桂国土资办〔2017〕123号)
作者简介: 王磊(1985-),男,硕士,高级工程师,主要从事地球化学研究工作。Email:68714655@qq.com
引用本文:   
王磊, 卓小雄, 吴天生, 凌胜华, 钟晓宇, 赵晓孟. 调查评价的土壤元素累积趋势预测——以广西南宁市西乡塘区为例[J]. 物探与化探, 2023, 47(1): 1-13.
WANG Lei, ZHUO Xiao-Xiong, WU Tian-Sheng, LING Sheng-Hua, ZHONG Xiao-Yu, ZHAO Xiao-Meng. Prediction of the soil element accumulation trends based on 1∶250 000 and 1∶50 000 geochemical surveys and assessments of land quality:A case study of Xixiangtang District, Nanning City, Guangxi zhuang Autonomous Region. Geophysical and Geochemical Exploration, 2023, 47(1): 1-13.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2023.2613      或      https://www.wutanyuhuatan.com/CN/Y2023/V47/I1/1
分析
指标
要求检
出限
1∶25万多目标区域
地球化学调查
1∶5万土地质量
地球化学评价
分析方法 实际检出限 分析方法 实际检出限
As 1.0 AFS 0.2 AFS 0.2
Cd 0.03 GFAAS 0.02 ICP-MS 0.02
Cr 5 XRF 3 XRF 2
Hg 0.0005 AFS 0.0004 AFS 0.0002
Pb 2.0 XRF 1.5 XRF 1.0
pH 0.10 ISE 0.08 ISE 0.01
Table 1  表层土壤调查样品分析方法及检出限
指标 1∶25万多目标区域地球化学调查 1∶5万土地质量地球化学评价
准确度 精密度
合格率
准确度 精密度
合格率
最小值 最大值 最小值 最大值 最小值 最大值 最小值 最大值
As -0.013 0.023 0.007 0.042 100% -0.061 0.086 0.002 0.061 100%
Cd -0.045 0.050 0.010 0.076 100% -0.096 0.090 0.003 0.080 100%
Cr -0.014 0.014 0.002 0.037 100% -0.062 0.069 0.010 0.048 100%
Hg -0.008 0.040 0.006 0.046 100% -0.100 0.098 0.007 0.072 100%
Pb -0.015 0.021 0.007 0.043 100% -0.097 0.085 0.009 0.069 100%
pH 0.01 0.10 100% 0.01 0.07 100%
Table 2  表层土壤调查样品一级标准物质分析准确度、精密度
指标 1∶25万多目标
区域地球化学调查
1∶5万土地
质量地球化学评价
As 93.33% 97.42%
Cd 86.67% 92.90%
Cr 98.67% 100.00%
Hg 86.67% 94.84%
Pb 98.67% 98.06%
pH 100.00% 100.00%
Table 3  表层土壤调查重复样合格率统计
Fig.1  研究区调查点位
数据集 数据量 w(As)/10-6 w(Cd)/10-6 w(Cr)/10-6 w(Hg)/10-6 w(Pb)/10-6 pH
WA 189 32.71 0.448 111.50 0.194 35.18 5.97
WB1(全区平均) 6524 37.68 0.439 154.49 0.222 37.49 5.73
WB2(调查配对点1km2) 697 37.51 0.467 156.89 0.221 38.27 5.81
WB3(分析配对点4km2) 189 36.47 0.456 154.31 0.218 37.78 5.82
Table 4  表层土壤调查样点元素含量及pH算术平均值统计
元素
类别
样本
数量
相关性分析 t检验
相关系数 Sig. t Sig.(双侧)
As(WB3)-As(WA) 189 0.91** 0 4.86 0
Cd(WB3)-Cd(WA) 189 0.91** 0 0.38 0.70
Cr(WB3)-Cr(WA) 189 0.92** 0 13.90 0
Hg(WB3)-Hg(WA) 189 0.90** 0 4.74 0
Pb(WB3)-Pb(WA) 189 0.96** 0 6.67 0
pH(WB3)-pH(WA) 189 0.66** 0 -2.81 0.01
Table 5  WB3WA中元素含量及pH相关性、t检验统计
Fig.2  WB3WA中元素含量及pH分布
端元 As Cd Cr Hg Pb
大气 0.722 0.081 0.986 0.009 1.668
Table 6  2017年西乡塘区大气干湿沉降重金属平均输入通量
端元 As Cd Cr Hg Pb
灌溉水 0.812 0.012 0.773 0.010 0.012
Table 7  2017年西乡塘区灌溉水重金属平均输入通量
端元 As Cd Cr Hg Pb
化肥 0.373 0.011 0.393 0.0003 0.185
Table 8  2017年西乡塘区化肥重金属平均输入通量
端元 As Cd Cr Hg Pb
农作物 花生 0.096 0.387 0.218 0.006 0.146
蔬菜瓜类 0.008 0.014 0.016 0.000 0.012
水稻籽实 0.356 0.088 0.240 0.009 0.083
香蕉 0.017 0.004 0.050 0.001 0.034
玉米 0.050 0.021 0.201 0.001 0.142
按种植面积
加权平均
0.030 0.015 0.051 0.001 0.032
Table 9  2017年西乡塘区农作物重金属平均输出通量
端元 As Cd Cr Hg Pb
灌溉排水 0.450 0.006 0.428 0.005 0.006
Table 10  2017年西乡塘区灌溉排水重金属平均输出通量
指数 污染物 分级类型
Pi=实测值/风险筛选值
Pj=实测值/风险管控值
i=As、Cd、Cr、Cu、Hg、Pb、Ni、Zn;
j =As、Cd、Cr、Hg、Pb
pi≤1
优先保护
pi>1,pj≤1
安全利用
pj>1
严格管控
Table 11  农用地土壤环境质量等级划分
指标 w(As) w(Cd) w(Cr) w(Hg) w(Pb) pH
10-6 10-6 10-6 10-6 10-6
含量 40.23 0.465 197.12 0.243 40.38 5.67
Table 12  单时段增量模型预测2027年土壤重金属元素含量
净输入通量 As Cd Cr Hg Pb
W 2.466 0.115 2.769 0.014 2.342
Table 13  通量模型土壤重金属年净输入通量
指标 w(As) w(Cd) w(Cr) w(Hg) w(Pb) pH
10-6 10-6 10-6 10-6 10-6
含量 36.58 0.461 154.43 0.219 37.88 5.67
Table 14  通量模型预测2027年土壤重金属元素含量
Fig.3  各元素不同输入途径对于输入输出通量的贡献比例
评价类别 评价对象 As Cd Cr Hg Pb 综合分级
优先保护 2007年(1∶25万) 126 133 152 189 186 99
2017年(1∶5万) 118 121 103 188 185 75
2027年(通量模型) 115 121 106 188 181 70
2027年(单时段增量) 107 113 89 187 177 56
安全利用 2007年(1∶25万) 63 56 37 0 3 90
2017年(1∶5万) 71 68 86 1 4 114
2027年(通量模型) 73 68 83 1 8 118
2027年(单时段增量) 81 76 100 2 12 132
严格管控 2007年(1∶25万) 0 0 0 0 0 0
2017年(1∶5万) 0 0 0 0 0 0
2027年(通量模型) 1 0 0 0 0 1
2027年(单时段增量) 1 0 0 0 0 1
优先保护点位占比 2007年(1∶25万) 66.67% 70.37% 80.42% 100.00% 98.41% 52.38%
2017年(1∶5万) 62.43% 64.02% 54.50% 99.47% 97.88% 39.68%
2027年(通量模型) 60.85% 64.02% 56.08% 99.47% 95.77% 37.04%
2027年(单时段增量) 56.61% 59.79% 47.09% 98.94% 93.65% 29.63%
Table 15  土壤环境质量分级点位数统计(n=189)
Fig.4  土壤环境质量综合等级
a—2007年调查数据;b—2017年调查数据;c—2027年通量模型预测数据;d—2027年单时段增量模型预测数据
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