【摘要】：黃金作為稀有的重金屬之一,以其儲量少和獨(dú)特理化性質(zhì)在國際金融經(jīng)濟(jì)和工業(yè)生產(chǎn)中起到了無可替代的作用。而金礦的開采會不可避免的引發(fā)一系列的環(huán)境問題,例如地面塌陷、土壤重金屬含量超標(biāo)以及粉塵污染等。現(xiàn)階段多使用化學(xué)方法測量土壤中重金屬元素含量,但是傳統(tǒng)的化學(xué)測定方法花費(fèi)較大且應(yīng)用面狹小,無法大面積的開展監(jiān)測,大大限制了對礦區(qū)周邊土壤環(huán)境的實(shí)時監(jiān)測。因此如何快速高效的對礦區(qū)周圍的土壤重金屬含量進(jìn)行監(jiān)測,同時預(yù)測重金屬元素對人體健康的危害等級,是當(dāng)前研究的熱門方向。而高光譜遙感技術(shù)以其精準(zhǔn)的分辨率和獲取數(shù)據(jù)的實(shí)時性,為土壤中重金屬元素含量的監(jiān)測提供了新的解決途徑,同時也為計算重金屬元素對人體健康危害的風(fēng)險值提供了數(shù)據(jù)基礎(chǔ)。本次研究以焦家金成礦帶作為主要研究區(qū)域,在國家自然科學(xué)基金項(xiàng)目“基于地表參量的污水灌溉區(qū)農(nóng)田生態(tài)安全遙感監(jiān)測研究”、“龍口礦區(qū)及周邊海岸帶遙感監(jiān)測研究”、“山東省焦家金成礦區(qū)及周邊礦區(qū)環(huán)境地質(zhì)遙感調(diào)查研究”、“黃河三角洲高效生態(tài)經(jīng)濟(jì)區(qū)(濰坊)海咸水入侵調(diào)查與監(jiān)控預(yù)警系統(tǒng)建設(shè)”以及“山東省國土資源遙感波譜庫建設(shè)”的支持下,結(jié)合高光譜遙感技術(shù)和地統(tǒng)計分析,對焦家金成礦帶及周邊地區(qū)的土壤重金屬含量進(jìn)行了反演預(yù)測,獲取了研究區(qū)域內(nèi)土壤中重金屬元素含量。同時借助健康風(fēng)險模型,計算了焦家金成礦帶內(nèi)重金屬元素對人體健康的風(fēng)險等級。研究的主要內(nèi)容和成果有:(1)在研究區(qū)域內(nèi)布置43個采樣點(diǎn),選取其中30個采樣點(diǎn)在實(shí)驗(yàn)室內(nèi)分別測取土壤光譜信息和各重金屬元素含量,建立土壤光譜信息和重金屬元素含量的多元回歸模型。通過檢測發(fā)現(xiàn)Cu和Zn元素最適合的模型為去包絡(luò)線模型,Hg、As、Pb元素最適合的模型為倒數(shù)對數(shù)模型,Cr元素最適合的模型為一階微分模型。(2)通過各元素的回歸模型反演剩余采樣點(diǎn)的重金屬元素含量,利用地統(tǒng)計分析得到各重金屬元素的空間分布結(jié)果,發(fā)現(xiàn):Cu、Hg、As、Cr、Pb和Zn元素含量區(qū)間分別在10.4-33.5、0.048-0.085、3.5-26.9、26.4-91.6、19.2-37.9、30.1-80.9 mg/kg范圍內(nèi),重金屬含量較高地區(qū)多位于中西部、東部和東北部地區(qū)。對比國家二級土壤有機(jī)物污染標(biāo)準(zhǔn),研究區(qū)域內(nèi)各重金屬元素含量均未超出標(biāo)準(zhǔn)。(3)將各重金屬元素空間分布結(jié)果與健康風(fēng)險模型相結(jié)合,得到研究區(qū)域內(nèi)各重金屬元素對人體健康的危害風(fēng)險等級分別為:As元素危險等級為I級;Cr元素風(fēng)險等級為II和III級;Cu、Hg、Pb和Zn元素風(fēng)險等級均小于I級,綜合評判后認(rèn)定焦家金成礦帶重金屬元素含量對人體健康的危害風(fēng)險等級為II級和III級。(4)焦家金成礦帶重金屬元素污染雖然并不明顯,但是已經(jīng)呈現(xiàn)聚集積累的趨勢,對人體健康已經(jīng)產(chǎn)生危害,需要引起人們的重視并在下一步的開采過程中采取相關(guān)的治理措施。
[Abstract]:As one of the rare heavy metals, gold plays an irreplaceable role in international financial economy and industrial production with its few reserves and unique physicochemical properties. Gold mining will inevitably lead to a series of environmental problems, such as ground collapse, heavy metal content in soil, dust pollution and so on. At present, chemical methods are often used to measure the content of heavy metals in soil, but the traditional chemical method is expensive and has a narrow application area, which limits the real-time monitoring of soil environment around the mining area. Therefore, how to quickly and efficiently monitor the content of heavy metals in the soil around the mining area and predict the harm grade of heavy metal elements to human health is a hot research direction at present. Hyperspectral remote sensing provides a new solution for monitoring the content of heavy metals in soil because of its accurate resolution and real-time data acquisition. At the same time, it also provides the data basis for calculating the risk value of heavy metal elements to human health. This research takes Jiaojia gold metallogenic belt as the main research area, "remote sensing monitoring research on farmland ecological security in sewage irrigation area based on surface parameters", "remote sensing monitoring research on Longkou mining area and its surrounding coastal zone" under the National Natural Science Foundation project, Environmental Geological remote Sensing investigation of Jiaojia Gold mineralization area and its surrounding area in Shandong Province, With the support of "investigation and monitoring and early warning system of sea salt water intrusion in the Yellow River Delta High efficiency Ecological Economic Zone (Weifang)" and "Construction of remote Sensing Spectrum Database of Land and Resources in Shandong Province", combined with hyperspectral remote sensing technology and geostatistical analysis, The contents of heavy metals in the soils of Jiaojiajin metallogenic belt and its surrounding areas were inversely predicted and the contents of heavy metals in the soil were obtained. At the same time, with the help of health risk model, the risk grade of heavy metal elements in Jiaojia gold metallogenic belt to human health was calculated. The main contents and results of the study are as follows: (1) 43 sampling sites are arranged in the study area, 30 of which are selected to measure the soil spectral information and the contents of heavy metals in the laboratory. A multivariate regression model of soil spectral information and heavy metal content was established. It is found that the most suitable model for Cu and Zn elements is the de-envelope model, and the most suitable model for Hg,As,Pb elements is the reciprocal logarithmic model. The most suitable model for Cr element is the first order differential model. (2) the content of heavy metal elements in residual sampling points is retrieved by regression model of each element, and the spatial distribution results of each heavy metal element are obtained by geostatistical analysis. It is found that: The contents of As,Cr,Pb and Zn were in the range of 10.4-33.5C 0.048-0.085N 3.5-26.926.4-91.6C 19.2-37.9C 30.1-80.9 mg/kg, respectively. The heavy metal contents were mostly located in the central and western regions of China. Eastern and northeastern regions Compared with the national secondary soil organic pollution standards, the contents of each heavy metal element in the study area did not exceed the standard. (3) the results of spatial distribution of each heavy metal element were combined with the health risk model. The risk levels of heavy metal elements to human health in the study area are as follows: As element hazard grade I; The risk level of Cr element is II and III. Both Cu,Hg,Pb and Zn element risk levels are smaller than I, After comprehensive evaluation, it was concluded that the hazardous risk of heavy metal elements in Jiaojia gold metallogenic belt to human health was II grade and III grade. (4) although the pollution of heavy metal elements in Jiaojia gold metallogenic belt was not obvious, it had shown a tendency of accumulation and accumulation. It is necessary to pay attention to human health and take relevant measures in the next mining process.
【學(xué)位授予單位】：山東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：X82;X87;X53

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