Trace metals distribution and their dependence on some physico-chemical parameters in creek sediment

The concentrations of the trace metals Mn, Zn, Cr, V, Co, Ni, Ba, Pb, Cu, Cd, As and Hg, their spatial distribution, and their correlation as a function of physico-chemical parameters were investigated for grab sediment samples collected from different locations across the Thane Creek, Mumbai, India. Hydride generation atomic absorption spectrometry, inductively coupled plasma atomic emission spectrometry, and differential pulse anodic stripping voltammetry were adopted for chemical analyses. Various geochemical indices were evaluated. The studied metal/metalloids were compared with sediment quality guideline values. Besides, the role of different physico-chemical parameters of the sediments such as pH, CaCO₃, cation exchange capacity, total carbon, and of the relative composition in respect to very coarse, coarse and medium sand, fine sand and very fine sand, silt and clay fraction were also critically investigated. Positive one-to-one correlations between fine sand and very fine sand, silt and clay, and total carbon with sediment metal concentrations have been noticed. Multiple regression analysis reveals strong positive correlations between sediment metal concentrations and total carbon content only.     

遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

室内甲醛污染影响因素的多元回归分析

本文在室内甲醛质量守恒定律基本公式合理推导的基础上,对影响甲醛浓度的主要因素做了正交实验。对实验数据进行多元回归分析,建立室内甲醛浓度预测模型。对模型做检验,检验结果表明,本文的预测模型能较好地预测室内空气中的甲醛浓度。     

基于社会科学统计程序(SPSS)回归性分析的尾矿库事故预测模型

基于社会科学统计程序(SPSS)软件的分析功能,对调查研究中获取的尾矿库案例进行数据提炼和分类编码,找出相关因子并进行回归性分析。最终目的是找出尾矿库各个因素的内在联系,建立简单的尾矿库事故模型,从而可以初步预测尾矿库事故发生的可能性。该预测模型为尾矿库事故的研究提出了新方法,对于防灾减灾以及保护人民生命财产安全起到了积极作用。     

高温烟气除尘滤料过滤性能检测及对比分析

对3大类不同过滤方式的高温烟气除尘滤料的压力损失、过滤速度、分级效率等性能指标进行测试对比分析,得到滤料在清洁和集尘条件下压力损失随过滤时间、粉尘负荷的变化规律.从过滤机理综合分析,集尘滤料的过滤分级效率明显高于清洁滤料过滤效率,为滤料选用提供理论依据.     

边坡变形时序非线性判定及混沌预测研究

以探讨边坡变形性质及混沌预测可行性为目的,基于混沌理论利用相空间重构技术对其变形时间序列进行混沌特征判定,试验显示变形系统具有混沌特性,可用混沌相关理论进行研究;基于混沌相空间重构技术,笔者构建了多种混沌预测模型进行混沌预计研究,分析各类模型的工程实际应用效果;针对单次监测时序预测精度较低的问题,提出累加时序预测方案,训练结果显示,短期预测精度变形累计值基本控制在5%以内,高程值预测相对误差均低于1%,预测精度较高,可以用于工程实际。     

Long-Term Relationship between Phosphorus Inputs and Wetland Phosphorus Concentrations in a Northern Everglades Marsh

Assessments of long-term relationships between changes innutrient inputs and wetland nutrient concentrations can becomplicated by fluctuations in other environmental factors aswell as by problems typical of long-term monitoring data.Consequently, statistical analysisof these types of data sets requirescareful consideration of environmental covariates, potentialbiases in the monitoring design, and irregularities caused bychanges in field sampling protocols. We evaluated therelationship between anthropogenic phosphorus (P) inputs andwater-column total P (TP) concentrations in a northernEverglades marsh by statistically analyzing available datacollected from several sampling programs over the past 20 years(1978–1997). Canal inputs of agricultural runoff contributemost of the P to the marsh and have produced a zone ofenrichment within the marsh during the past few decades.Regression analyses showed that both canal and marsh TPconcentrations increased during the 1980s and then decreased inthe 1990s. However, the statistical relationship between canal Pinputs and marsh TP, while significant, generally was weakexcept for marsh locations adjacent to the canal. Strongerrelationships existed between marsh TP and hydrologic parameterssuch as marsh water depth, which is controlled by changes inweather patterns and marsh management. In particular, dryconditions during the 1980s may have contributed to observedincreases in marsh P concentrations and the movement of a P`front' further into the marsh. Higher rainfall and water depthsand agricultural best management programs initiated during the1990s have been associated with reduced P concentrations incanal waters entering the marsh. While it is anticipated thatthis reduction eventually will result in lower marsh TPconcentrations, this effect is not yet evident, possibly due tointernal loading of P from enriched marsh soils. Our findingsillustrate some of the environmental factors that can complicateattempts to develop empirical relationships between P inputs andwetland P concentrations and to use such relationships to forecast changesin marsh concentrations based on past monitoring data alone.     

关于植物中氟化物测定结果的计算

针对植物中氟化物测定时由于绘制校准曲线的标准溶液体积与分析样品的定容体积不一样而引出的结果计算时的某些问题,提出了正确的计算方法和建议。     

Step-up multiple regression model to compute Chlorophyll a in the coastal waters off Cochin, southwest coast of India

The interaction effects of abiotic processes in the production of phytoplankton in a coastal marine region off Cochin are evaluated using multiple regression models. The study shows that chlorophyll production is not limited by nutrients, but their physiological regulations (responses to nutrients, pH, temperature and salinity) are mainly responsible for the increased biological production. The model explaining 77% of variability for chlorophyll a production is indicative of preconditioning of the coastal waters. The phytoplankton production is found to be sensitive to the environment, which varies seasonally. Further, the study suggests that supply of organic matter and grazing of zooplankton (not included) would improve the model efficiency. Despite this, the good agreement in the computed and measured chlorophyll a values shows that step-up multiple regression model is a useful tool to understand the influence of environmental variables on the production of phytoplankton in these coastal waters.