文章摘要
程菁靓,赵龙,杨彦,侯红,孙在金,马瑾.我国长江中下游水稻产区铅污染分区划分方法研究[J].农业环境科学学报,2019,38(1):70-78.
我国长江中下游水稻产区铅污染分区划分方法研究
Classification methods for typical lead-contaminated rice production areas of the middle and lower Yangtze River in China
投稿时间:2018-07-03  
DOI:10.11654/jaes.2018-0853
中文关键词: 水稻产区划分    富集系数  物种敏感性分布
英文关键词: classification of rice production area  lead  enrichment coefficient  species sensitivity distribution
基金项目:国家重点研发计划项目(2017FYD0801101-2)
作者单位E-mail
程菁靓 常州大学环境与安全工程学院, 江苏 常州 213000
中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012 
 
赵龙 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012 zhaolong1227@126.com 
杨彦 常州大学环境与安全工程学院, 江苏 常州 213000 yy129129@163.com 
侯红 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
孙在金 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
马瑾 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
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中文摘要:
      以我国典型水稻产区——长江中下游平原为研究对象,在系统收集文献中20种水稻品种可食部位及其对应土壤中重金属铅(Pb)的协同调研数据基础上,综合考虑了水稻品种和土壤理化性质的影响,探讨了基于物种敏感性分布(SSD)法来划分水稻"宜产、限产、禁产"三区的方法,并以保护不同比例水稻品种反推出了各划分区的土壤Pb含量阈值。研究结果表明:该典型水稻产区的土壤pH与水稻Pb的富集系数间呈负相关,相关系数为-0.46(P<0.05),土壤有机碳(SOC)与水稻Pb的富集系数间呈正相关,相关系数为0.91(P<0.01),同时由pH和SOC两个变量所建立的回归模型可以解释水稻富集系数83.20%的变异;4种典型情景土壤中的水稻品种敏感性顺序分布基本一致;长江中下游平原区划分水稻"宜产、限产、禁产"三区的土壤Pb含量分别为≤ 14.81mg·kg-1,14.81~185.24 mg·kg-1和≥ 185.24 mg·kg-1。"宜产、限产、禁产"划分方法具有较好的科学性、普适性及可操作性,可推广至全国水稻产区的分区划分,将为我国农用地土壤的风险管理提供重要的技术支撑。
英文摘要:
      We selected the middle and lower reaches of the Yangtze River basin, a typical rice-producing area in China, as the research object. We considered the effects of rice varieties and soil physico-chemical properties, and we investigated the techniques for classifying rice-producing areas as "suitable yield" "restricted yield" and "forbidden yield" using the species sensitivity distribution(SSD) method. This decision was based upon the collection of collaborative survey data regarding lead contamination of 20 rice varieties and the corresponding soil. Furthermore, the soil lead content threshold for the three classification areas was derived to protect different proportions of rice variety. The results show that the soil pH of this typical rice-producing area negatively correlated to the lead enrichment coefficient of rice. The correlation coefficient was -0.46(P<0.05). The soil organic carbon was positively correlated to the lead enrichment coefficient of rice, and the correlation coefficient was 0.91(P<0.01). The regression model, derived from pH and soil organic carbon variables, can explain the 83.20% variation of rice enrichment factors. The sequence of rice variety sensitivity distribution in the four typical scenarios was consistent. The soil lead content in the middle and lower reaches of the Yangtze River basin was less than or equal to 14.81 mg·kg-1, 14.81~185.24 mg·kg-1 and greater than or equal to 185.24 mg·kg-1. Generally, this classification method shows good rationality, universality, and operability. Furthermore, it can be extended to the classification of rice-producing areas nationwide. It also provides important technical support opportunities for the risk management of agricultural land in China.
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