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1.
由乌鲁木齐市环境科研监测中心站历时两年完成的"用树叶树皮含硫量监测和评价乌鲁木齐市大气SO2污染研究"课题,4月17日在乌鲁木齐市通过鉴定。利用树叶树皮监测和评价大气SO2污染研究工作在国内外已开展过,但利用大叶榆和白腊树对硫酸盐化速率进行研究和评价SOz污染未见报道,此项研究在新疆尚属空白。本项研究结果表明,不同树叶吸收SO2的程度不同,同种树木叶片吸收SO。的能力大于皮部,被研究树种的树叶含硫量与非采暖期的大气硫酸盐化速率和SO2之间均存在着极其显著的正相关关系。被研究树种在植物休眠期的皮流含量与采暖期大气…  相似文献   

2.
大气污染对城市绿化植物叶片叶绿素含量的影响   总被引:8,自引:0,他引:8  
研究了南阳市城市大气对该市5种常见城市绿化植物叶片叶绿素(a、b)含量比例(Ca/Cb)以及叶片叶绿素总含量(Ct)的影响。通过研究发现,污染严重的南阳卷烟厂区域植物叶片叶绿素Ca/Cb值相对较高,叶绿素总含量(Ct)相对较低;无污染的对照区域(南阳师范学院院内绿化区)植物叶片叶绿素Ca/Cb值相对较低,叶片叶绿素总含量(Ct)相对较高。通过数据分析,进一步得出了5种常见城市绿化植物抗大气污染能力的大小:女贞>大叶黄杨>月季>金叶女贞>三叶草。  相似文献   

3.
泰州市降水主要特征及酸雨成因浅析   总被引:4,自引:0,他引:4  
对泰州市1996年—2000年降水主要特征及酸雨成因进行了分析。结果表明,泰州市酸雨出现频率高,5年来降水pH均值均<5.6,降水酸度和酸雨出现频率无明显变化;降水中化学成分以SO42-为主,NO3-质量浓度值呈上升趋势;酸雨出现频率的季节变化规律为:冬、春季>秋季>夏季,与SO2在不同季节质量浓度变化规律较一致;酸雨的形成可能受本地大气污染物和异地大气污染物的共同影响;酸性降水的形成与气象条件有关。  相似文献   

4.
拉萨市大气污染分布特征及气象影响因子分析   总被引:4,自引:1,他引:3  
以2001~2006年拉萨市的空气环境质量自动监测结果为基础数据,阐明拉萨市区主要大气污染物SO2、NO2、PM10的逐日变化、季节变化以及年变化特征.在此基础上,分析了大气污染物浓度与气象条件的关系.结果表明,除NO2日夜差别不大之外,SO2与PM10质量浓度分别存在典型的单峰、双峰变化;各污染物质量浓度具有冬强夏弱的季节变化规律;就年平均而言,SO2浓度增加,PM10浓度降低,NO2浓度变化不显著,各污染物有明显的突变现象.大多数气象要素与污染物浓度具有较好的负相关,即满足降水量增加、温度升高、相对湿度增大会导致污染物浓度减小的规律,气象要素量级与大气污染天数多少也存在密切关系.  相似文献   

5.
一、前言近年来,南京市大气二氧化硫的污染现状及成因已有不少报道.但是有关大气二氧化硫、三氧化硫与市区主要绿化树木悬铃木叶片含硫量之间有什么样的关系?1988年7月和9月对市区各不同功能行政区悬铃木叶片含硫量进行了采样、分析;并同时对空气中三氧化硫进行了监测,根据已存的SO_2资料,探讨了它们之间的相关性,取得了满意的结果.二、方法  相似文献   

6.
贵阳市每年向大气排放约30万吨的SO_2,年污染平均负荷量为每平方公里2.54吨,高于全国平均水平(2吨/平方公里),并且因排放集中。使城区污染负荷量高达66.21吨/平方公里,超过全国平均年污染负荷量32.1倍。贵阳市的大气污染呈明显的“煤烟型”,大气中SO_2含量高,降水酸度大,pH最低为3.20,形成以贵阳市为中心的黔中强酸雨区。为了进一步研究大气中SO_2和酸雨对植物的影响,本研究选择了对大气污染较敏感的苔藓、地衣类及英国梧桐(悬铃木)作为大气污染的生物指标和指示植物,并对苔藓、地衣进行种类、多度、盖度和频度的统计,对英国梧桐进行叶片含硫量测定和伤斑面积计算,探讨这些植物与污染程度的关系,据此绘出该地区大气污染图,并与监测资料进行了综合对比分析。  相似文献   

7.
2001年~2008年及奥运会期间天津市大气污染特征分析   总被引:1,自引:1,他引:0  
根据天津市大气质量监测数据,对2001年~2008年及奥运会期间天津市大气污染特征和主要大气污染物的变化规律进行了分析。结果表明,2001年~2008年天津市的PM10、SO2和NO2污染总体呈下降趋势,但质量浓度仍相对较高。2008年8月奥运会期间天津市PM10和SO2质量浓度达到国家空气质量二级标准,NO2质量浓度达到国家空气质量一级标准,空气质量良好。天津市PM10污染相对稳定,SO2和NO2的污染分布呈现明显的季节性,时间上表现为冬强夏弱。气象条件对污染物浓度影响明显,沙尘、大雾等天气可使污染物浓度急剧升高。  相似文献   

8.
乌鲁木齐市大气污染时空分布规律研究   总被引:4,自引:1,他引:3  
李沫 《干旱环境监测》2009,23(4):223-226
为掌握乌鲁木齐市大气污染时空分布规律,利用近年乌鲁木齐市大气污染物的浓度最新资料,详尽分析了其空气质量的年际变化和空间分布特征。统计了2008年各污染物日、月变化规律。结果表明,近年乌鲁木齐市城区大气污染物质量浓度具有明显时空分布规律,即大气污染物质量浓度冬春季大于夏秋季,PM10和SO2浓度夜间大于白天。在空间分布上,PM10和SO2南部区域最高,中部次之,市区北部最轻,NO2则呈现出由北向南逐渐升高的分布特征。  相似文献   

9.
杭州市酸雨污染现状及成因分析   总被引:10,自引:0,他引:10  
对杭州市1998年—2002年的降水监测数据进行了统计分析。结果表明,2002年杭州市区酸雨频率为73.6%,降水pH均值为4.68,临安酸雨频率高达97.5%,降水pH均值为4.04,其余几个县(市)降水酸度均<5.60。杭州市有82.1%面积属重酸雨区。指出,杭州市气象条件不利于大气中SO2、NOx的扩散,土壤扬尘不能对酸雨的形成起有效的缓冲作用,因此只有通过调整能源结构,从源头控制煤质(含硫量),严格控制机动车尾气污染,以减少SO2、NOx排放量。  相似文献   

10.
为研究大同市大气颗粒物质量浓度与水溶性离子组成特征,于2013年2、7、9、12月,分别对大同市及其对照点庞泉沟国家大气背景点进行了PM2.5及PM10的采样,通过超声萃取-IC法测定了样品中的9种水溶性离子,结果表明,大同市大气颗粒物污染1、4季度重于2、3季度,PM2.5季度均值全年均未超标,PM10仅第1季度超标1.4倍,污染状况总体良好,PM2.5与PM10相关系数R为0.75,说明大同市颗粒物污染有较为相近的来源,且不同季节均以粗颗粒物为主;大同市PM2.5中水溶性离子浓度分布为SO2-4、NO-3、NH+4Cl-、Ca2+K+、Na+F-、Mg2+,PM10中Ca2+浓度仅次于SO2-4、NO-3,控制扬尘将有效降低PM10的浓度;PM2.5及PM10中的9种水溶性离子在不同季度的浓度与颗粒物浓度分布规律类似,1、4季度较高,2、3季度较低;由阴阳离子平衡计算结果可知,相关性方程的斜率K为1.045,表明大同市大气颗粒物中阳离子相对亏损,大气细粒子组分偏酸性。NO-3与SO2-4浓度比值均小于1,大同市以硫酸型污染为主,大气中的SO2-4主要来源于人类活动排放。  相似文献   

11.
基于实测光谱的海河悬浮物浓度反演研究   总被引:1,自引:0,他引:1  
悬浮物浓度是评价水质优劣的重要指标之一。以天津滨海新区海河为研究区域,进行光谱数据测量和水体样本采集,并在实验室进行水质参数提取,得到归一化光谱反射率和光谱一阶微分数据。然后对光谱测量数据和悬浮物浓度实测值进行相关性分析,发现896 nm归一化光谱反射率和光谱反射率比值(R_(896)/R_(546))与悬浮物浓度相关性较好。最后,分别建立单波段、波段比值和一阶微分函数拟合模型,进行对比分析。结果表明,基于R_(896)/R_(546)的二次多项式模型拟合效果最好,方差齐性检验(F)值也是最高的,可用于该地区水体的悬浮物浓度反演和预测。  相似文献   

12.
This paper presents a study dealing with soil organic carbon (SOC) estimation of soil through the combination of soil spectroscopy and multivariate stepwise linear regression. Soil samples were collected in the three sub-regions, dominated by brown calcic soil, in the northern Tianshan Mountains, China. Spectral measurements for all soil samples were performed in a controlled laboratory environment by a portable ASD FieldSpec FR spectrometer (350–2,500 nm). Twelve types of transformations were applied to the soil reflectance to remove the noise and to linearize the correlation between reflectance and SOC content. Based on the spectral reflectance and its derivatives, hyperspectral models can be built using correlation analysis and multivariable statistical methods. The results show that the main response range of soil organic carbon is between 400 and 750 nm. Correlation analysis indicated that SOC has stronger correlation with the second derivative than with the original reflectance and other transformations data. The two models developed with laboratory spectra gave good predictions of SOC, with root mean square error (RMSE) <5.0. The use of the full visible near-infrared spectral range gave better SOC predictions than using visible separately. The multivariate stepwise linear regression of second derivate model (model A) is optimal for estimating SOC content, with a determination coefficient of 0.894 and RMSE of 0.322. The results of this research study indicated that, for the grassland regions, combining soil spectroscopy and mathematical statistical methods does favor accurate prediction of SOC.  相似文献   

13.
环境卫星CCD影像在太湖沉水植物监测中的应用   总被引:1,自引:0,他引:1       下载免费PDF全文
利用环境一号卫星 CCD影像,综合现场巡视情况,对2014年1—5月太湖梅梁湖水域的沉水植被区域进行分析与研究,分别取沉水植物、水华、地表植被与水体4个样本区域,对它们的光谱反射率曲线进行分析,得到沉水植物光谱反射率曲线相比其他样本区域独特的结论。并根据此特征,结合基于提取样本运行决策树的方法,以2014年5月1日为例,提取出了太湖梅梁湖水域沉水植物的分布区域与面积。  相似文献   

14.
土壤盐分含量(SSC)是评价土地退化和肥力水平的重要指标,实现SSC状态和空间分异的快速准确监测对区域环境的优化管理极为关键。选取潍北平原为研究区,野外采集233处土壤样品并获取同时相Sentinel-2多光谱影像,进一步将特征光谱波段和构建的最优光谱指数作为输入自变量,测试得到的SSC实测值为因变量,最后将空间关联函数引入到随机森林中去建立基于空间关联随机森林算法的SSC遥感估算模型,完成区域尺度上的SSC反演估算与空间制图。结果表明:影像的B3、B8和B11是SSC的特征波段,通过波段比值变换能够增强卫星光谱信号对SSC的吸收响应,筛选得到的最优光谱指数分别为RI34(波段3和波段4的反射率比值)、RI711(波段7和波段11的反射率比值)、ND611(波段6和波段11的反射率归一化值)和D45(波段4和波段5的反射率差值);仅用特征波段或最优光谱指数来构建模型不能取得满意的SSC估算精度,空间关联随机森林模型的SSC估算精度要高于随机森林模型;在将上述特征波段和最优光谱指数共同输入空间关联随机...  相似文献   

15.
Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline-alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.  相似文献   

16.
以某重金属矿区3个水域(a、b、c)作为研究区,采集Aster卫星传感器的遥感监测数据,再运用分光辐射光谱仪测定标准板与目标水体,计算目标水体的光谱反射率,分析各区域水体遭受重金属污染时的光谱反射特征,实现基于光谱分析的重金属污染废水遥感监测。结果表明:a区域内水体重金属污染程度由深水区向浅水区逐步增强,水体呈现出橙红色;b区域内水体重金属污染程度由浅水区向深水区逐步增强,水体呈现为棕红色;c区域内水体未受到重金属污染,整个区域内水体为铜绿色。该结果与现场采集的各区域水体遭受重金属污染的情况一致。  相似文献   

17.
在河北省保定市白洋淀区域采集115个土壤样品进行重金属含量分析和室内光谱测量,分别将BP神经网络、随机森林、决策树、多元线性回归、K近邻回归、AdaBoost回归和偏最小二乘回归法应用于全部原始波谱数据和基于双层随机森林选择后的波段数据。结果表明,基于原始波谱数据的土壤重金属Zn元素含量的反演模型精度较低,而通过双层随机森林选择出光谱数据中与土壤重金属Zn信息相关的波段,减轻了网络模型的过拟合问题,提高了模型预测精度;与其他模型比较,结合双层随机森林和BP神经网络构建的反演模型对研究区土壤重金属Zn含量预测效果最佳。  相似文献   

18.
对太湖地区近10余年来共32景Landsat TM/ETM遥感影像进行大气校正处理,获得地表反射率影像,在这些影像上采集了分布在不同片区、不同发生季节、不同集聚程度的蓝藻水华样区,提取了不同蓝藻水华的可见一近红外波段反射率数据.统计表明蓝藻水华在TM 4波段的反射率有较宽的动态范围,能定量反映蓝藻集聚程度,TM 2也是...  相似文献   

19.
This paper presents a novel method for estimating black-soil organic matter (SOM) in the black-soil zone of northeast China from hyperspectral reflectance models. Traditional black-soil property measurements are relatively slow, but the pressures of agricultural production and environmental protection require a quick method to collect black-soil organic matter content. SOM estimation using soil hyperspectral reflectance models can meet this requirement, based on the spectral characteristics of black-soil in Northeast China. On the basis of the spectral reflectance and its derivatives, hyperspectral models can be built using correlation analysis and multivariable statistical methods. The concepts of curvature and ratio indices are also applied to compare and test the stability and accuracy of data modeling. The results show that the response of black-soil spectral reflectance from 400-1,100 nm to organic matter content is more marked than that from 1,100-2,500 nm. Specifically, the main response range of black-soil organic matter is between 620-810 nm, with a maximal spectral response at 710 nm. By comparing different models, we found that the normalized first derivate model is optimal for estimating SOM content, with a determination coefficient of 0.93 and root mean squared errors (RMSE) of 0.18%.  相似文献   

20.
In this study, we examined the ability of reflectance spectroscopy to predict some of the most important soil parameters for irrigation such as field capacity (FC), wilting point (WP), clay, sand, and silt content. FC and WP were determined for 305 soil samples. In addition to these soil analyses, clay, silt, and sand contents of 145 soil samples were detected. Raw spectral reflectance (raw) of these soil samples, between 350 and 2,500-nm wavelengths, was measured. In addition, first order derivatives of the reflectance (first) were calculated. Two different statistical approaches were used in detecting soil properties from hyperspectral data. Models were evaluated using the correlation of coefficient (r), coefficient of determination (R 2), root mean square error (RMSE), and residual prediction deviation (RPD). In the first method, two appropriate wavelengths were selected for raw reflectance and first derivative separately for each soil property. Selection of wavelengths was carried out based on the highest positive and negative correlations between soil property and raw reflectance or first order derivatives. By means of detected wavelengths, new combinations for each soil property were calculated using rationing, differencing, normalized differencing, and multiple regression techniques. Of these techniques, multiple regression provided the best correlation (P?<?0.01) for selected wavelengths and all soil properties. To estimate FC, WP, clay, sand, and silt, multiple regression equations based on first(2,310)-first(2,360), first(2,310)-first(2,360), first(2,240)-first(1,320), first(2,240)-first(1,330), and raw(2,260)-raw(360) were used. Partial least square regression (PLSR) was performed as the second method. Raw reflectance was a better predictor of WP and FC, whereas first order derivative was a better predictor of clay, sand, and silt content. According to RPD values, statistically excellent predictions were obtained for FC (2.18), and estimations for WP (2.0), clay (1.8), and silt (1.63) were acceptable. However, sand values were poorly predicted (RDP?=?0.63). In conclusion, both of the methods examined here offer quick and inexpensive means of predicting soil properties using spectral reflectance data.  相似文献   

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