發(fā)布時(shí)間：2018-07-10 04:19

  本文選題：礦區(qū) + 土壤-小麥�。� 參考：《中國(guó)礦業(yè)大學(xué)》2017年碩士論文

【摘要】：礦產(chǎn)資源開發(fā)利用改變了區(qū)域生態(tài)系統(tǒng)的物質(zhì)循環(huán)和能量流動(dòng),造成了嚴(yán)重的生態(tài)破壞和環(huán)境污染。其中,礦區(qū)土壤重金屬污染是嚴(yán)重的問題之一。論文設(shè)計(jì)并實(shí)施2014、2015、2016年三期野外自然條件下的礦區(qū)土壤-小麥重金屬遷移模擬實(shí)驗(yàn),分析Cr添加場(chǎng)地、Pb添加場(chǎng)地、Zn添加場(chǎng)地和正常對(duì)照?qǐng)龅?種添加重金屬Cr、Pb、Zn和2種常見重金屬Cd、Cu在土壤-小麥系統(tǒng)中的遷移、富集特征。研究可為礦區(qū)土壤環(huán)境質(zhì)量改善和糧食安全調(diào)控提供數(shù)據(jù)基礎(chǔ)和理論依據(jù)。主要結(jié)論如下:(1)基于野外模擬實(shí)驗(yàn)的基礎(chǔ)數(shù)據(jù),分析了礦區(qū)土壤-小麥重金屬遷移、富集特征。①四類場(chǎng)地土壤5種重金屬隨時(shí)間的變化規(guī)律存在差異,小麥中5種重金屬含量大體先減后增。②添加重金屬Cr、Pb、Zn在土壤和小麥中含量數(shù)據(jù)的離散程度均要大于Cd、Cu。③三類添加場(chǎng)地土壤和小麥中Cr、Pb、Zn均高于正常對(duì)照?qǐng)龅?說明人為添加重金屬行為直接或間接地促進(jìn)了重金屬元素向土壤-小麥系統(tǒng)中轉(zhuǎn)化和遷移。④三類添加場(chǎng)地土壤Cr、Pb、Zn存在由含量高處向含量低處遷移的現(xiàn)象,符合溶質(zhì)運(yùn)移規(guī)律。⑤四類場(chǎng)地小麥對(duì)Zn的富集能力最強(qiáng)、Pb的富集能力最弱。(2)建立了礦區(qū)土壤-小麥重金屬遷移模型,并對(duì)徐州柳新礦區(qū)進(jìn)行數(shù)值模擬。①四類場(chǎng)地土壤-小麥中重金屬含量間絕大部分相關(guān)系數(shù)|r|0.5、灰色度fG(r)0.5,并不存在簡(jiǎn)單的線性相關(guān)關(guān)系。②四類場(chǎng)地土壤和小麥中重金屬含量的最優(yōu)曲線回歸模型以二次曲線模型和拋物線模型居多。Zn和Cu曲線回歸模型的相關(guān)性較顯著,而Cr、Pb、Cu曲線回歸模型的相關(guān)性不顯著。除Cr以外,正常對(duì)照?qǐng)龅刂亟饘偾�回歸模型的相關(guān)系數(shù)歲要高于其他三種添加場(chǎng)地。③小麥中5種重金屬的作物富集因子PAF與土壤相應(yīng)重金屬濃度數(shù)學(xué)模型的相關(guān)系數(shù)R2均大于0.5,說明兩者之間的相關(guān)性顯著,建立的數(shù)學(xué)模型可行。其中,小麥中Cd的PAF與土壤重金屬Cd濃度數(shù)學(xué)模型的相關(guān)系數(shù)R2達(dá)到0.918,呈現(xiàn)極顯著相關(guān)性。④優(yōu)選的分配估計(jì)模型對(duì)徐州柳新礦區(qū)煤矸石復(fù)墾場(chǎng)地、粉煤灰復(fù)墾場(chǎng)地和對(duì)照?qǐng)龅匦←溨蠧r的預(yù)測(cè)效果相對(duì)較好、Cd的預(yù)測(cè)效果相對(duì)較差。(3)首先,評(píng)價(jià)了土壤-小麥系統(tǒng)中重金屬生態(tài)危害程度,四類場(chǎng)地土壤-小麥中5種重金屬總體處于輕度污染水平。在此基礎(chǔ)上,設(shè)計(jì)并實(shí)施礦區(qū)土壤重金屬Cr、Pb、Zn修復(fù)植物篩選實(shí)驗(yàn),為礦區(qū)土壤重金屬污染提供了一種修復(fù)植物篩選辦法,并初步得出百喜草和狗牙根可做為土壤Cr的修復(fù)植物,苜蓿和落花生可做為土壤Pb的修復(fù)植物,東南景天和佛甲草對(duì)土壤Zn的修復(fù)效果不明顯。
[Abstract]:The exploitation and utilization of mineral resources have changed the material circulation and energy flow of the regional ecosystem and caused serious ecological damage and environmental pollution. Among them, soil heavy metal pollution is one of the serious problems in mining area. This paper designs and implements a simulation experiment of heavy metal transport between soil and wheat in mining area under three natural conditions in the field in 2014, 2015 and 2016. The migration and enrichment characteristics of three kinds of heavy metals, CrPbPbZn and two common heavy metals, CD and Cu, in the soil-wheat system were analyzed. The study can provide data basis and theoretical basis for soil environmental quality improvement and food security control in mining area. The main conclusions are as follows: (1) based on the basic data of field simulation experiments, the changes of five heavy metals over time in soil and wheat in mining area were analyzed. The contents of 5 kinds of heavy metals in wheat decreased first, then increased 2. 2 in soil and wheat. The dispersion of the data of CRPbZn in soil and wheat was higher than that in the soil of three kinds of addition sites of CdCu.3 and in wheat, which was higher than that in normal control sites. The results showed that anthropogenic addition of heavy metals directly or indirectly promoted the transformation and migration of heavy metal elements into soil-wheat system. In accordance with the solute migration rule, wheat has the strongest enrichment ability of Zn and the weakest enrichment ability of Pb. (2) the heavy metal migration model of soil-wheat in mining area was established. Numerical simulation of Xuzhou Liuxin mining area. 1.Most correlation coefficient of heavy metal content between soil and wheat in four kinds of sites is r 0.5, grey degree fG (r) 0.5. There is no simple linear correlation between soil and wheat in four types of sites. The correlation between the quadratic curve model and the parabola model was significant in the optimal curve regression model of heavy metal content. The correlation between the curve regression model and the Cu curve regression model was significant. However, there was no significant correlation between the curve regression model of CrPbCU and Cu. Except for Cr, The correlation coefficient of curve regression model of heavy metals in normal control site was higher than that of the mathematical model of soil heavy metal concentration and PAF of 5 heavy metals in the other three kinds of wheat. 3. The correlation coefficient R2 of PAF was higher than that of the mathematical model of soil concentration of heavy metals. All of them are more than 0.5, which means that there is a significant correlation between them. The established mathematical model is feasible. Among them, the correlation coefficient R2 between PAF of CD in wheat and CD concentration in soil reached 0.918, which showed highly significant correlation. 4 optimal allocation estimation model for coal gangue reclamation site in Xuzhou Liuxin mining area. The prediction effect of Cr and CD in fly-ash reclamation site and control field was relatively good. (3) the ecological damage degree of heavy metals in soil-wheat system was evaluated. Five kinds of heavy metals in four kinds of soil-wheat were in the level of light pollution. On the basis of this, the screening experiment of remediation plants for heavy metal Cr Pb Zn in the soil of mining area was designed and carried out, which provided a method for the screening of remediation plants for heavy metal pollution in the soil of mining area, and it was preliminarily concluded that Bahia grasses and Doggeana could be used as remediation plants for soil Cr. Alfalfa and peanut can be used as soil Pb remediation plants.
【學(xué)位授予單位】：中國(guó)礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：S512.1;X53;X751

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 賈趙恒;羅瑤;沈友剛;劉凡;蔡崇法;譚文峰;邱國(guó)紅;;大冶龍角山礦區(qū)農(nóng)田土壤重金屬形態(tài)分布及其來源[J];農(nóng)業(yè)環(huán)境科學(xué)學(xué)報(bào);2017年02期

2 秦樊鑫;魏朝富;鐘守琴;黃先飛;龐文品;姜鑫;;Soil heavy metal(loid)s and risk assessment in vicinity of a coal mining area from southwest Guizhou, China[J];Journal of Central South University;2016年09期

3 張廈;宋靜;高慧;張強(qiáng);劉贛;;回歸模型法推導(dǎo)油菜田土壤Cd限值的不確定性[J];環(huán)境科學(xué)研究;2016年08期

4 劉亞納;朱書法;魏學(xué)鋒;苗娟;周鳴;關(guān)鳳杰;;河南洛陽(yáng)市不同功能區(qū)土壤重金屬污染特征及評(píng)價(jià)[J];環(huán)境科學(xué);2016年06期

5 劉巍;楊建軍;汪君;王果;曹月娥;;準(zhǔn)東煤田露天礦區(qū)土壤重金屬污染現(xiàn)狀評(píng)價(jià)及來源分析[J];環(huán)境科學(xué);2016年05期

6 劉育辰;王莉淋;伍鈞;楊剛;漆輝;鄧仕槐;;四川城市生活垃圾重金屬污染狀況及來源分析[J];環(huán)境工程學(xué)報(bào);2015年12期

7 荀久玉;;遼寧省污灌區(qū)土壤重金屬銅、鉻、鎘和汞的形態(tài)研究[J];青海環(huán)境;2015年02期

8 楊啟良;武振中;陳金陵;劉小剛;王衛(wèi)華;劉艷偉;;植物修復(fù)重金屬污染土壤的研究現(xiàn)狀及其水肥調(diào)控技術(shù)展望[J];生態(tài)環(huán)境學(xué)報(bào);2015年06期

9 石潤(rùn);吳曉芙;李蕓;馮沖凌;李韻詩(shī);;應(yīng)用于重金屬污染土壤植物修復(fù)中的植物種類[J];中南林業(yè)科技大學(xué)學(xué)報(bào);2015年04期

10 劉碩;吳泉源;張龍龍;蔡?hào)|全;周歷媛;劉娜;曹學(xué)江;;基于野外實(shí)測(cè)光譜的污灌區(qū)土壤重金屬污染快速監(jiān)測(cè)[J];安全與環(huán)境學(xué)報(bào);2015年02期

相關(guān)博士學(xué)位論文 前7條

1 宋鳳敏;陜西典型鐵尾礦庫(kù)區(qū)土壤重金屬遷移及其修復(fù)研究[D];西北農(nóng)林科技大學(xué);2016年

2 傅曉文;鹽漬化石油污染土壤中重金屬的污染特征、分布和來源解析[D];山東大學(xué);2014年

3 王恒;吉林省土壤—水稻系統(tǒng)環(huán)境質(zhì)量分析評(píng)估及重金屬?gòu)?fù)合污染研究[D];中國(guó)科學(xué)院研究生院（東北地理與農(nóng)業(yè)生態(tài)研究所）;2014年

4 王成;長(zhǎng)三角地區(qū)土壤—小麥系統(tǒng)微量元素遷移的地球化學(xué)特征[D];南京大學(xué);2013年

5 楊金香;木本植物修復(fù)煤礦復(fù)墾區(qū)重金屬遷移規(guī)律研究[D];安徽理工大學(xué);2012年

6 高輝;幾類常用非線性回歸分析中最優(yōu)模型的構(gòu)建與SAS智能化實(shí)現(xiàn)[D];中國(guó)人民解放軍軍事醫(yī)學(xué)科學(xué)院;2012年

7 董霽紅;礦區(qū)充填復(fù)墾土壤重金屬分布規(guī)律及主要農(nóng)作物污染評(píng)價(jià)[D];中國(guó)礦業(yè)大學(xué);2008年

相關(guān)碩士學(xué)位論文 前5條

1 付紅艷;關(guān)于變異系數(shù)、偏度系數(shù)和峰度系數(shù)的U統(tǒng)計(jì)量檢驗(yàn)法[D];吉林師范大學(xué);2014年

2 魏本杰;微生物強(qiáng)化植物修復(fù)重金屬污染土壤[D];湖南工業(yè)大學(xué);2014年

3 徐國(guó)棟;土壤電動(dòng)修復(fù)中重金屬遷移的模擬研究[D];蘭州大學(xué);2014年

4 甘國(guó)娟;土壤—水稻系統(tǒng)重金屬遷移特征與區(qū)域污染風(fēng)險(xiǎn)評(píng)價(jià)[D];中南林業(yè)科技大學(xué);2013年

5 寧雄義;重金屬礦區(qū)生態(tài)風(fēng)險(xiǎn)評(píng)價(jià)研究[D];浙江大學(xué);2006年

，

本文編號(hào)：2112023