【作者】 朱仁果；

【导师】 肖化云；

【作者基本信息】 南昌大学 ， 环境工程， 2010， 硕士

【摘要】 随着产业经济的发展,大气硫沉降带来了一系列的生态破坏和经济损失,引起人们的高度重视。为了探讨苔藓作为监测植物指示大气硫污染的可靠性,研究江西省大气硫沉降的空间分布以及追溯其大气硫源,本论文测定了江西省19个采样点的112个细叶小羽藓(H. microphyllum (Hedw.))组织硫含量和69个苔藓组织硫同位素值。对江西省苔藓组织硫含量和硫同位素值进行了空间分析,研究了苔藓组织硫含量与大气硫沉降量,苔藓组织硫含量与大气SO2浓度,苔藓组织硫含量与苔藓组织氮含量,苔藓苔藓组织硫同位素值与雨水硫同位素值以及苔藓组织硫同位素值(δ34S)与煤样硫同位素值(634S)的相关性,同时结合显著性差异分析,聚类分析等数理统计方法。探讨了江西省苔藓组织硫含量和硫同位素值的空间分布特征,山区和城市苔藓组织硫含量和硫同位素值的差异以及南昌市和江西省的大气硫源。研究结果表明：(1)通过对苔藓组织硫含量的分析发现,在大气硫浓度高的地区苔藓组织硫含量也高,说明苔藓植物可以作为监测植物指示大气硫污染。江西省苔藓组织硫含量表现出从西南往东北的递增规律,反映出了江西省大气硫湿沉降量的空间分布规律。对市区苔藓和郊区苔藓的硫含量进行t检验,其中南昌市和贵溪市市区苔藓组织硫含量和郊区苔藓组织硫含量有显著性差异(P<0.001),且市区苔藓组织硫含量明显高于郊区苔藓组织硫含量,说明这两个城市市区苔藓受到了点污染源的影响。(2)江西省苔藓组织S/N比变化范围为0.074-0.524,与中国南部城市苔藓组织S/N变化范围是0.11-0.19一致。但贵溪冶炼厂的苔藓组织的S/N为0.316±0.181(0.195-0.524)远高于中国南部城市苔藓组织的S/N值。用直线S/N=0.15把江西省采样点分为两组。在江西省,只有贵溪市贵溪冶炼厂周围的苔藓组织S/N>0.15(组Ⅰ),表明苔藓组织吸收了相对大量的大气硫(过量的硫)。而其它采样点苔藓组织S/N<0.15(组Ⅱ),说明其它采样点均是硫缺乏或者说是氮过量。南昌市雨水中SO42-/NH4+的变化范围是1.15-1.37,正好是南昌市苔藓组织S/N的变化范围(0.08-0.15)的14倍。表明雨水的SO42-/NH4+比值决定了苔藓组织的S/N比值。(3)结合有限的雨水硫同位素资料发现南昌大学前湖校区苔藓组织硫同位素值(0.55‰-0.56‰,平均值0.55+0.01‰)和雨水硫酸根硫同位素值(-3.55-3.91‰,平均值-0.33±1.78‰)相接近,说明苔藓组织硫同位素值能指示其长期吸收的硫来源。通过对南昌市市区,郊区,景区(梅岭),电厂周围苔藓组织以及煤的δ34S值进行单因素方差分析,发现南昌市市区和郊区受相同硫源的影响,而景区和电厂周围分别受不同大气硫源的共同影响,并且发现南昌市电厂燃煤不仅能影响南昌市大气硫沉降还能影响到郊区乃至于景区。(4)江西省苔藓硫同位素平均值为+4.71±3.25‰(-3.58-10.40‰)。其中以上饶苔藓组织硫同位素值最高9.60±0.50‰,丰城苔藓组织硫同位素最低-3.31±0.43‰,山区苔藓组织硫同位素值(6.23±2.14‰)高于市区苔藓组织硫同位素值(0.86±2.41‰),且存在显著性差异(p<0.001)。说明山区和城市受不同来源硫的影响。(5)本研究用聚类分析方法对江西省19个采样点苔藓组织634S值进行了分析,把江西省苔藓组织634S值分成了4组,分析发现每组苔藓组织有着特异性的硫含量和硫同位素值,说明每组受不同大气硫源的影响,同时还通过聚类分析还发现江西省不同城市中工业生产使用的煤的来源不同。(6)江西省苔藓组织硫同位素和苔藓组织硫含量1/S呈线性相关性y=0.76+1.21x(R2=0.16,p<0.001)。根据双硫源模型,结合聚类分析和江西省苔藓组织δ34S值的空间分布规律,表明江西省大气硫沉降可能受本地人为硫源(主要是煤燃烧)和外源重硫的共同影响。更多还原

【Abstract】 With the industry economic development, atmospheric sulfur deposition caused a series of ecological damage and economic losses which have caused people’s attention. In order to explore the reliability of moss used as biological indicator to monitor atmospheric sulfur pollution,the spatial distribution of atmospheric sulfur deposition of Jiangxi Province and trace atmospheric sulfur source. This paper packed 112 moss (H.microphyllum (Hedw.)) in 19 sampling sites of Jiangxi Province and determine tissue sulfur content and sulfur isotope values of moss.This paper used spatial analysis to analysis tissue sulfur content and sulfur isotope of moss in Jiangxi province and the relationship of tissues sulfur content of lichen and the amount of atmospheric sulfur deposition, tissue sulfur content of moss and concentrations of SO2 and atmospheric,tissue sulfur content and tissue nitrogen content, sulfur isotope values of rain and the moss tissue sulfur isotope and tissue sulfur isotope (δ34S) of moss and coal sulfur isotope(δ34S).Combined with the correlation significant difference analysis, cluster analysis,and other mathematical statistics,investigate spatial distribution of sulfur content of mosses and sulfur isotope in Jiangxi province,significant difference sulfur content and sulfur isotope of the mountain and urban lichen tissue and atmospheric sulfur source of Nanchang and Jiangxi Province. The results show:(1) Where atmospheric sulfur concentration is high, tissue sulfur content of moss is also high, indicating bryophyte plants can be used as bio-indicator to monitor atmospheric sulfur pollution. Tissue the sulfur content of moss in Jiangxi province increased from southwest to the northeast, reflecting the spatial distribution of atmospheric sulfur wet deposition in Jiangxi Province. Trough t-test, significant difference (P<0.001) between urban and suburban tissue sulfur content of moss in Guixi and Nanchang cities were found Tissue sulfur content of the urban moss moss tissue was significantly higher than that of suburban, indicated that the atmospheric sulfur source of this two cities were caused by point sources.(2) Tissue S/N ratio of moss varied from 0.074 to 0.524 in Jiangxi Province fall into the range of tissue S/N of moss in China’s southern cities,which is 0.11 0.19.However, S/N of moss around Guixi Smelter was 0.316±0.181 (0.195-0.524) which is much significant higher than S/N of moss in China’s southern cities. Sampling points of Jiangxi Province is divided into two groups by Linear S/N=0.15. In Jiangxi Province, only the S/N of moss tissue in Guixi City> 0.15 (groupⅠ), show that the moss tissue absorbs relatively large amount of atmospheric sulfur (excess of sulfur). The other group moss tissue S/N<0.15 (groupⅡ), indicating other samples are the lack of sulfur or nitrogen excess.SO42-/NH4+ of Nanchang in rain vary from 1.15 to 1.37, exactly S/N of moss tissues in Nanchang city in the range of 0.08 and 0.15,which is 14 times lower than the ratio of SO42-/NH4+ in rainfall,showing that the ratio of SO42-/NH4+ in rainfall determines S/N ratio of tissues of mosses.(3) With limited water sulfur isotope data,we can found tissues sulfur isotope of moss in Qianhu Lake is 0.55‰-0.5’6‰(average 0.55±0.01‰) and sulfate sulfur isotope of rainfall is-3.55-3.91‰(average-0.33±1.78‰) which is close in Nanchang, indicating the value of lichen tissue sulfur isotopes can indicate the sulfur source of its long-term absorption. ANOVA analysis showed that urban and suburban Nanchang subject to the same source of sulfur, while the Meling and power plant were effected by different atmospheric sulfur sources combined, and found that Sulphid from the coal-fired power plant in Nanchang not only can affect atmospheric sulfur deposition in urban but also can affect the suburbs and even in the scenic area.(4) The average sulfur isotope moss is+4.71±3.25‰(-3.58-10.40‰) Jiangxi Province. Among them, tissues sulfur isotope of moss in Shangrao is the highest(9.60±0.50‰), the lowest is tissue sulfur isotope of moss in Fengcheng (-3.31±0.43‰). Mountain tissue sulfur isotope of moss (6.23±2.14‰) is higher than urban tissue sulfur isotope (0.86±2.41‰), and significant difference exist(p <0.001) indicating the mountains area and cities are affected by different sources of sulfur.(5) This study used cluster analysis to analysis 112 samples of Jiangxi province.δ34S value of the moss tissues. Analysis showed that each group has a specific lichen tissue sulfur content and sulfur isotope values, indicating each subject to different sources of atmospheric sulfur impact. At the same time through the cluster analysis We can also found that industrial production in Jiangxi Province in different cities use different sources of coal.(6) Tissue sulfur isotope and sulfur content (1/S) of moss showed a linear correlation y= 0.76+1.21 x (R2= 0.16, p<0.001) in Jiangxi province. According to two-sulfur source model and the result of the clustering analysis and spatial distribution ofδ34S values of moss in Jiangxi Province may be affected by a combined atmospheric sulfur source in Jiangxi Province, which is locals sulfur sources (mainly caused by coal burning) and exogenous sulfur source.更多还原