Spatial Distribution Characteristics and Influencing Factors of Soil Cadmium Content in Jieyang of Guangdong Province

doi:10.19657/j.geoscience.1000-8527.2020.01.08

Abstract

Abstract:

In this paper, 1,330 topsoil (0-20 cm) samples and 331 deep soil (150-200 cm) samples were collected from Jieyang, Guangdong, China. The enrichment characteristics, spatial distribution, structural characteristics and influencing factors of soil cadmium content in the study area were systematically analyzed by the methods of enrichment factor, GIS spatial analysis, semi-variogram fitting and analysis of variance. The results showed that the average cadmium content in the topsoil was 0.09 mg/kg, which was higher than the soil background value of the area, but lower than “Soil Environmental Quality Risk Control Standard for Farmland Soils (Trial)(GB 15618-2018)”. According to the enrichment factor method, the cadmium content in topsoil of the study area was mainly slightly and moderately polluted. From the structural characteristics, the cadmium content in the topsoil of the study area was moderately spatially correlated. The high value areas of cadmium in topsoil of Jieyang City were mainly distributed in the eastern and southern areas where human activities were intensive. Land use types, soil parent materials and soil types were important factors affecting cadmium content in surface soil. Under different land use types, the cadmium content in construction land was the highest; In different parent materials, the cadmium content in the Quaternary sediments was significantly higher than other parent materials; In different soil types, the cadmium content in paddy soil was relatively high.

Key words: soil cadmium, spatial distribution, influencing factor, Jieyang city, Guangdong

CLC Number:

P595
X142

WANG Juanheng, WEN Hanhui, CAI Limei, LUO Jie, WANG Shuo, WANG Qiushuang, MU Guizhen, JIANG Huihao. Spatial Distribution Characteristics and Influencing Factors of Soil Cadmium Content in Jieyang of Guangdong Province[J]. Geoscience, 2020, 34(01): 88-96.

Figures/Tables 9

References 33

[1]	BI X Y, FENG X B, YANG Y G, et al. Quantitative assessment of cadmium emission from zinc smelting and its influences on the surface soils and mosses in Hezhang County, southwestern China[J]. Atmospheric Environment, 2006,40(12):4228-4233.
[2]	金立新, 侯青叶, 包雨函, 等. 德阳镉污染农田区生态安全性及居民健康风险评价[J]. 现代地质, 2008,22(6):984-989.
[3]	LIANG J, FENG C T, ZENG G M, et al. Atmospheric deposition of mercury and cadmium impacts on topsoil in a typical coal mine city, Lianyuan, China[J]. Chemosphere, 2017,189(12):198-205.
[4]	郭笃发. 环境中铅和镉的来源及其对人和动物的危害[J]. 环境科学进展, 1994,2(3):71-76.
[5]	刘旭, 顾秋蓓, 杨琼, 等. 广西象州与横县碳酸盐岩分布区土壤中Cd形态分布特征及影响因素[J]. 现代地质, 2017,31(2):374-385.
[6]	NISHIJO M, NAKAGAWA H, SUWAZONO Y, et al. Causes of death in patients with Itai-itai disease suffering from severe chro-nic cadmium poisoning: a nested case-control analysis of a follow-up study in Japan[J]. BMJ Open, 2017,7(7):1-7.
[7]	YAMAGAMIA T, EZAKIB T, MORIGUCHI J. Low-level cadmium exposure in Toyama City and its surroundings in Toyama prefecture, Japan, with references to possible contribution of shellfish intake to increase urinary cadmium levels[J]. Science of the Total Environment, 2006,362(1):56-67.
[8]	VEGA F A, MATIAS J M, ANDRADE M L, et al. Classification and regression trees (carts) for modelling the sorption and retention of heavy metals by soil[J]. Journal of Hazardous Materials, 2009,167(13):615-624.
[9]	MAMAT Z, YIMIT H, JI R Z A, et al. Source identification and hazardous risk delineation of heavy metal contamination in Yanqi basin, northwest China[J]. Science of the Total Environment, 2014,493(3):1098-1111.
[10]	庄国泰. 我国土壤污染现状与防控策略[J]. 中国科学院院刊, 2015,30(4):477-483.
[11]	孙慧, 毕如田, 袁宇志, 等. 广东省土壤镉含量影响因子解析与评估[J]. 环境科学学报, 2016,36(11):4173-4183.
[12]	郑袁明, 罗金发, 陈同斌, 等. 北京市不同土地利用类型的土壤镉含量特征[J]. 地理研究, 2005,24(4):542-548.
[13]	江东鹏, 张宝春. 粤东揭阳市环境污染控制对策研究[J]. 环境科学与管理, 2010,35(10):43-45.
[14]	罗杰. 广东省韩江三角洲土壤污染物源辨析及其环境承载力 [D]. 武汉: 中国地质大学(武汉), 2016: 1-166.
[15]	胡秀芳. 湿法消解-石墨炉原子吸收光谱法在土壤镉测定中的应用[J].中国标准化, 2018(S1):181-184,196.
[16]	姚朝英, 任兰. 石墨炉原子吸收法测定土壤中镉的测量不确定度评定[J]. 化学分析计量, 2007,16(1):11-13.
[17]	田瑜. 粉末压片制样X射线荧光光谱法测定土壤中的几种重金属[J]. 安阳工学院学报, 2018,17(6):24-27.
[18]	中国地质调查局. 多目标区域地球化学调查规范(DD2005-01)[EB/OL].(2005-10-01)[2019-03-10]. http://www.doc88.com/p-5495876006057.html.
[19]	范晓婷, 蒋艳雪, 崔斌, 等. 富集因子法中参比元素的选取方法:以元江底泥中重金属污染评价为例[J]. 环境科学学报, 2016,36(10):3795-3803.
[20]	胡恭任, 于瑞莲. 应用地积累指数法和富集因子法评价324国道塘头段两侧土壤的重金属污染[J]. 中国矿业, 2008,17(4):47-51.
[21]	BERGAMASEHI L, RIZZIO E, VALCUVIA M G. Determination of trace elements and evaluation of their enrichment factors in Himalayan lichens[J]. Environmenta1 Pollution, 2002,120(1):137-144.
[22]	FANG G C, WU Y S, CHANG S Y, et al. Size distributions of ambient air particles and enrichment factor analyses of metallic elements at Taichung Harbor near the Taiwan Strait[J]. Atmospheric Research, 2006,81(4):320-333.
[23]	JIANG Y X, CHAO S H, LIU J W, et al. Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province, China[J]. Chemosphere, 2017,168(12):1658-1668.
[24]	郄建荣. 两项土壤污染防治新标准发布[J]. 湖南农业, 2018(10):11.
[25]	ZHANG S W, SHEN C Y, CHEN X Y, et al. Spatial interpolation of soil texture using compositional Kriging and regression Kriging with consideration of the characteristics of compositional data and environment variables[J]. Journal of Integrative Agriculture, 2013,12(9):1673-1683.
[26]	仝致琦, 段海静, 阮心玲, 等. 路旁土壤公路源重金属含量空间分布数值模型的探讨[J]. 环境科学学报, 2014,34(4):996-1002.
[27]	靳诚, 陆玉麒. 基于县域单元的江苏省经济空间格局演化[J]. 地理学报, 2009,64(6):713-724.
[28]	蔡立梅, 马瑾, 周永章, 等. 珠江三角洲典型区农业土壤镍的空间结构及分布特征[J]. 中山大学学报(自然科学版), 2008,47(4):100-104.
[29]	舒彦军, 张立亭. 求解半变异函数的常用方法与新方法研究[J]. 测绘与空间地理信息, 2012,35(5):24-27.
[30]	姚荣江, 杨劲松, 刘光明. 土壤盐分和含水量的空间变异性及其CoKriging估值: 以黄河三角洲地区典型地块为例[J]. 水土保持学报, 2006,20(5):133-138.
[31]	张庆利, 史学正, 黄标, 等. 南京城郊蔬菜基地土壤有效态铅、锌、铜和镉的空间分异及其驱动因子研究[J]. 土壤, 2005,37(1):41-47.
[32]	刘强, 林乃明, 沙春鹏, 等. 钢铁材料电镀镉的研究现状[J]. 表面技术, 2017,46(1):146-157.
[33]	刘丽萍, 乙小娟, 杨雪芬. 合成染料中金属元素的ICP测定结果分析[J]. 预防医学情报杂志, 2001,17(2):96-97.

等级	富集因子	污染程度	所占比例/ %
I	≤ 1	未污染	28.88
II	>1~2	轻微污染	32.98
III	>2~5	中度污染	31.39
IV	>5~20	显著污染	6.75
V	>20~40	强烈污染	0
VI	>40	极强污染	0

等级	富集因子	污染程度	所占比例/ %
I	≤ 1	未污染	28.88
II	>1~2	轻微污染	32.98
III	>2~5	中度污染	31.39
IV	>5~20	显著污染	6.75
V	>20~40	强烈污染	0
VI	>40	极强污染	0

类型	表层土壤			深层土壤
类型	样品数	镉含量/(mg/kg)	变幅/(mg/kg)	样品数	镉含量/(mg/kg)	变幅/(mg/kg)
农用地	339	0.07 c	0.01~0.36	71	0.06 c	0.01~0.51
建筑用地	350	0.10 a	0.01~1.90	93	0.08 a	0.01~0.51
林地及未利用地	641	0.09 b	0.01~1.39	167	0.09 b	0.01~1.70
第四纪沉积物	354	0.13 b	0.01~1.39	86	0.09 a	0.01~1.70
粉砂岩	134	0.08 a	0.01~0.46	36	0.07 b	0.01~0.29
页岩	10	0.09 a	0.04~0.36	4	0.06 b	0.02~0.22
凝灰岩	119	0.09 a	0.01~0.55	34	0.06 b	0.01~0.31
花岗岩	713	0.08 a	0.01~1.90	171	0.05 b	0.01~0.51
风沙土	26	0.04 b	0.01~0.15	8	0.03 b	0.01~0.07
赤红壤	813	0.08 b	0.01~0.99	199	0.06 b	0.01~0.51
水稻土	471	0.11 a	0.01~1.90	121	0.12 a	0.01~1.70
黄壤	20	0.08 b	0.01~0.36	3	0.03 b	0.01~0.22

类型	表层土壤			深层土壤
类型	样品数	镉含量/(mg/kg)	变幅/(mg/kg)	样品数	镉含量/(mg/kg)	变幅/(mg/kg)
农用地	339	0.07 c	0.01~0.36	71	0.06 c	0.01~0.51
建筑用地	350	0.10 a	0.01~1.90	93	0.08 a	0.01~0.51
林地及未利用地	641	0.09 b	0.01~1.39	167	0.09 b	0.01~1.70
第四纪沉积物	354	0.13 b	0.01~1.39	86	0.09 a	0.01~1.70
粉砂岩	134	0.08 a	0.01~0.46	36	0.07 b	0.01~0.29
页岩	10	0.09 a	0.04~0.36	4	0.06 b	0.02~0.22
凝灰岩	119	0.09 a	0.01~0.55	34	0.06 b	0.01~0.31
花岗岩	713	0.08 a	0.01~1.90	171	0.05 b	0.01~0.51
风沙土	26	0.04 b	0.01~0.15	8	0.03 b	0.01~0.07
赤红壤	813	0.08 b	0.01~0.99	199	0.06 b	0.01~0.51
水稻土	471	0.11 a	0.01~1.90	121	0.12 a	0.01~1.70
黄壤	20	0.08 b	0.01~0.36	3	0.03 b	0.01~0.22