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城乡融合区土壤元素地球化学特征与源解析:以天府新区青龙片区为例
摘要点击 2900  全文点击 1215  投稿时间:2021-05-16  修订日期:2021-08-11
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中文关键词  城乡融合区  土壤地球化学  源解析  正定矩阵因子分析法(PMF)  青龙片区
英文关键词  urban-rural integration area  soil geochemistry  source apportionment  positive matrix factorization  Qinglong Area
作者单位E-mail
刘书淮 成都理工大学地球科学学院, 成都 610059 2019020133@stu.cdut.edu.cn 
王德伟 中国地质调查局成都地质调查中心, 成都 610081 155343514@qq.com 
施泽明 成都理工大学地球科学学院, 成都 610059
成都理工大学地学核技术四川省重点实验室, 成都 610059 
 
唐亮 成都理工大学地球科学学院, 成都 610059
成都理工大学地学核技术四川省重点实验室, 成都 610059 
tangliang17@cdut.edu.cn 
章凤英 成都理工大学地球科学学院, 成都 610059  
廖程 成都理工大学地球科学学院, 成都 610059  
李晓雨 成都理工大学地球科学学院, 成都 610059  
徐文斌 成都理工大学地球科学学院, 成都 610059  
中文摘要
      城乡融合区是城市与农村的连接区域,是城市农产品最重要供给区,其土壤地球化学性质影响因素复杂.为此,以四川省天府新区青龙融合区为研究对象,共采集了395个土壤样品,测定了pH值、有机质(SOM)、全钾(TK)、速效钾(AK)、全氮(TN)、碱解氮(AN)、全磷(TP)、有效磷(AP)、Se、B、V、Zn、Mn、Mo、Ni、Co、As、Cd、Cr、Cu、Hg和Pb等指标.结果表明,TN、Se、Hg和TP含量相较成都经济区背景值明显偏高,Cr、Mn、pH和TK明显偏低.结合相关性统计、地统计学及PMF源解析研究,得到重金属元素主要受四类源的影响,大小关系为:自然源(32%)>工业源(30%)>农业源(25%)>交通源(14%).此外,从地形、工业园边界、农户密度和交通流量等角度对源解析结果进行了验证,认为研究区Mo、Co、Ni和V的含量主要受坡度影响(母岩暴露),Hg和As的含量受农业活动影响,Cd、Mn、Cr和Zn的含量主要受工业生产影响,Pb、Zn、Cu、Cd和Hg的含量与交通运输有关.
英文摘要
      The Qinglong Area of Tianfu New District in China is the connection area of Chengdu city, Sichuan Province, which dominantly supports the primary agricultural products for the metropolis. The soil quality, therefore, has been deteriorating in recent decades due to the intensive planting and industrial pollution. Thus, the evaluation of soil quality and the identification of the pollution sources are significant for sustainable soil planting and regulation. To this end, 395 soil samples were collected, and the parameters of pH, soil organic matter (SOM), total potassium (TK), available potassium (AK), total nitrogen (TN), alkali-hydrolyzable nitrogen (AN), total phosphorus (TP), available phosphorus (AP), Se, B, V, Zn, Mn, Mo, Ni, Co, As, Cd, Cr, Cu, Hg, and Pb were analyzed. The results revealed that TN, Se, Hg, and TP were obviously higher than the background value of the Chengdu Economic Zone, and the Cr, Mn, pH, and TK were depleted. The combination of correlation statistics, geostatistics, and positive matrix factorization (PMF) source analysis revealed that heavy metal enrichments were mainly affected by four sources, namely natural sources (32%)>industrial sources (30%)>agricultural sources (25%)>traffic sources (14%). Likewise, the source apportionments were verified regarding topography, industrial boundary, farmer density, and traffic flow. It was estimated that Mo, Co, Ni, and V were affected by slope; the enrichment of Hg and As was the result of agricultural activities; Cd, Mn, Cr, and Zn were affected by industrial waste diffusion; and Pb, Zn, Cu, Cd, and Hg were related to transportation. To a certain extent, agricultural fertilization and pesticide application have partially controlled soil fertility and pollution (Hg and As).

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