水中藻类对连续流动法测定总氮结果的影响

以天津市河道、水库为研究对象,在藻类增殖期采用连续流动法与碱性过硫酸钾消解法对水体中总氮进行比对监测,同时分析水中藻类分类和藻细胞密度。试验表明:虽然两种方法测定总氮的结果精密度基本相同,但二者之间的系统误差存在显著差异,连续流动法较碱性过硫酸钾消解法的测定结果低5.4%。两种方法测定总氮结果的相对偏差与水体中藻细胞密度呈正相关性,当水体中藻细胞密度﹥2.41×108L-1时,对连续流动法测定总氮的结果产生显著影响,相对偏差超过标准规范要求。     

水中总氮测定方法存在问题的研究及改进

碱性过硫酸钾消解紫外分光光度法测定水中总氮采用的消解器皿是玻璃比色管,易造成空白偏高、结果偏低等问题。采用双圆柱状的消解杯对水样进行消解。结果表明,消解杯消解水中总氮,线性相关系数均大于0.999,检出限为0.05 mg/L,相对标准偏差小于5%,相对误差为0.88%~1.00%;改进后的消解器皿具有较好的精密度和准确度,能够更加准确测定水中总氮的含量。     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

淮河支流污染物综合降解系数动态测算

确定河流污染物综合降解系数动态变化规律对提高水环境容量测算精度和水环境管理具有重要意义。通过现场模拟法,采用一维稳态模型测算了淮河支流洪河五沟营-塔桥乡河段COD、氨氮和总磷在枯水期、平水期和丰水期的综合降解系数,COD、氨氮和总磷降解系数在各水期的关系为枯水期平水期丰水期,提出了建议值并利用实测浓度对计算结果进行了检验,结果表明,不同水期综合降解系数吻合情况较好。     

The Impact of Agriculture On Dissolved Nitrogen and Phosphorus Cycling in Temperate Ecosystems

Although most research has focussed on inorganic nutrient forms of nitrate (NO^-₃) and phosphorus (PO³₄) in runoff and receiving waters, nitrogen loss from agricultural land can also occur in organic and ammonium-nitrogen form; phosphorus losses, although often dominated by particulate transport, may occur in soluble organic and inorganic form. Furthermore, fluxes between different species may take place during transport from the land to the stream and as a result of in-stream, in-river or in-lake transformations. Knowledge of the spatial and temporal variation in all nitrogen species and phosphorus fractions in a drainage basin is therefore essential if the wider environmental significance of elevated nutrient concentrations in natural waters are to be assessed. This paper reviews recent work on N and P losses from agricultural land and presents some results from two intensive agricultural catchments: Slapton, Devon and the river Windrush catchment in the Cotswolds.     

Tolerance of calluna vulgaris and peatland plant communities to sulphuric acid deposition

Critical loads offer a unique way of evaluating impacts of acid deposition by quantifying environmental sensitivity. The critical loads of acidity for UK peat soils have been based upon an arbitrary reduction in pH of 0.2 units. This chemical shift needs to be better related to adverse effects on sensitive biological receptors. It is known that effective precipitation pH equates closely to soil solution pH, and the latter is directly linkable to biotic effects of pH change. On continuation of a long-term experiment assessing impacts of simulated acid rain on peat microcosms in a realistic outdoor environment, Calluna vulgaris continued to flourish at acid deposition loads well above the existing critical load. Calluna plants were harvested and analysed, and acid deposition treatments to the microcosms continued to allow natural vegetation to regenerate. A diverse mixture of moorland plants and bryophytes established at acidity treatments well above the existing critical load, and only a very high acid load resulted in no natural regeneration. A critical effective rain pH value of 3.6 is suggested as a basis for setting critical loads. At this pH, Calluna grows well, and a healthy diverse vegetation community re-establishes when harvested. It is suggested that the peat critical load should be set at the acid load that, at any specific site, would result in a mean effective precipitation pH of 3.6.     

Prenatal prediction of childhood-onset spinal muscular atrophy (SMA) in Turkish families

Childhood-onset spinal muscular atrophy (SMA) is one of the most common neurodegenerative genetic disorders. SMN1 is the SMA-determining gene deleted or mutated in the majority of SMA cases. There is no effective cure or treatment for this disease yet. Thus, the availability of prenatal testing is important. Here we report prenatal prediction for 68 fetuses in 63 Turkish SMA families using direct deletion analysis of the SMN1 gene by restriction digestion. The genotype of the index case was known in 40 families (Group A) but unknown in the remaining 23 families (Group B). A total of ten fetuses were predicted to be affected. Eight of these fetuses were derived from Group A and two of these fetuses were from Group B families. Two fetuses from the same family in Group A had the SMNhyb1 gene in addition to homozygous deletion of the NAIP gene. One fetus from Group A was homozygously deleted for only exon 8 of the SMN2 gene, and further analysis showed the presence of both the SMN1 and SMNhyb1 genes but not the SMN2 gene. In addition, one carrier with a homozygous deletion of only exon 8 of the SMN1 gene was detected to have a SMNhyb2 gene, which was also found in the fetus. To our knowledge, these are the first prenatal cases with SMNhyb genes. Follow-up studies demonstrated that the prenatal predictions and the phenotype of the fetuses correlated well in 33 type I pregnancies demonstrating that a careful molecular analysis of the SMN genes is very useful in predicting the phenotype of the fetus in families at risk for SMA. Copyright © 2002 John Wiley & Sons, Ltd.     

Diffusion pollution from livestock and poultry rearing in the Yangtze Delta,China

BACKGROUND: The Yangtze Delta is one of the most developed regions in China and includes Shanghai, eight cities in Jiangsu province and eight cities in Zhejiang province. Meat consumption in this region has increased with economic growth, and most of the consumed meat is produced locally. The water quality of surface waters has deteriorated in recent years. An example was the huge blue-green algae bloom in Tai Lake in late May 2007, which affected millions of people's daily drinking water. However, animal husbandry is considered to be one of the main pollution sources. METHODS: Pollutants (NH3-N, total phosphorus (TP), and total nitrogen (TN)) excreted by livestock and poultry, and the resultant COD (chemical oxygen demand) and BOD (biochemical oxygen demand), were estimated using two different methods based on different data sets. RESULTS: The number of livestock and poultry has remained stable in the Yangtze Delta over the four years from 1999 to 2002, with the average number of pigs, cattle, sheep and poultry being 21.1 M, 0.4 M, 7.7 M and 597.6 M, respectively. Pollutants in livestock and poultry excreta estimated by Method I were: 0.12 Mt NH3-N, 0.11 Mt TP and 0.29 Mt TN, resulting in COD and BOD of 1.34 Mt and 1.30 Mt, respectively, while the estimations based on Method II were: 0.18 Mt NH3-N, 0.15 Mt TP and 0.40 Mt TN, resulting in COD and BOD of 1.95 Mt and 1.80 Mt, respectively. DISCUSSION: Pollutants excreted annually by livestock and poultry in the Yangtze Delta are estimated to be: 0.17 Mt NH3-N, 0.16 Mt TP and 0.42 Mt TN, giving rise to a COD of 1.86 Mt and a BOD of 1.72 Mt. Approximately 25% of this pollution was estimated to enter water bodies, which means that the annual pollutant load is 43,700 t NH3-N, 39,400 tTP, 104,600t TN with a COD of 465,000 tand a BOD of 430,100 t. Pollutants from animal husbandry were similar in magnitude to those from industrial wastewater. Pigs produced the most pollution, followed by poultry, cattle and sheep. The pollution load from animal husbandry in the Yangtze Delta is about twice the average level of the whole of China. CONCLUSIONS: Domestic wastewater was the main pollution source in the Yangtze Delta, followed by pollution from raising livestock and poultry and from industrial wastewater. The pollution load in Shanghai and Jiaxing were the greatest, followed by 7 cities of Jiangsu province (except Suzhou) and other cities of Zhejiang province and Suzhou. Pigs and poultry produced about 90% of the total pollutants from animal husbandry. RECOMMENDATIONS AND PERSPECTIVES: The local governments, especially in Shanghai and Jiaxing, should focus their attention on the pollution produced by livestock and poulrry. Controlling pollution from pigs and poultry will have the greatest impact in this region. Control of pollution will be facilitated by the development of large-scale livestock and poultry farming units and a shift away from small scale husbandry.     

Long term changes in the eutrophication process in a shallow Mediterranean lake ecosystem of W. Greece: response after the reduction of external load

Lake Pamvotis is a shallow Mediterranean lake located in Western Greece near the city of Ioannina. The lake has been recognized as an internationally important conservation site under European Community legislation due to its rich biodiversity. However, during the last three decades the trophic status of the lake has changed as a result of anthropogenic activity (among others irrigation and domestic sewage discharge), resulting in serious problems. Here we present data about the long-term development in eutrophication of Lake Pamvotis. Water samples were collected and analyzed (water temperature, pH, dissolved oxygen, nutrients, chlorophyll-a) during three monitoring periods: 1985-1989, 1998-1999, 2004-2005. The high nutrient concentrations in the lake water during the three monitoring periods, as well as its eutrophic to hypertrophic status reflect the degree of impact anthropogenic activity has had on the lake. Commencement of a restoration plan in 1995-1996, involving sewage diversion, led to a reduction in external nutrient load and consequently to lower in-lake nutrients and Chlorophyll-a concentrations. Orthophosphate concentration decreased by about 87%, nitrates fell below 1.20mg/l, whilst the total reduction of inorganic N compounds showed a weaker downward trend, fluctuating between 0.39 and 1.24mg N/l with an average value of 0.76mg N/l. However, after a short-term recovery the eutrophic status of the lake remains eight years later (2004-2005), suggesting the importance of the internal loading process and the absence of the top-down effect of fish. This study provides evidence for the need of greater restoration efforts utilized in Mediterranean shallow lakes.     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。