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.     

北京市空气质量及其与能源消费结构的动态关联

运用模糊集理论中的Euclidean权距离评价2002—2011年北京市空气质量。根据最大隶属度原则确定空气质量等级值,结合灰色系统理论中的关联动态矩阵分析法,研究北京市主要大气污染物与9种能源消费因子的动态关系。结果表明,2002、2004—2007年北京市空气质量处于Ⅲ级,2003、2008—2011年处于Ⅱ级,空气质量由劣到优的年份排序为2002、2011、2010、2006、2007、2009、2008、2005、2004、2003年,2003、2008年空气质量得到改善,2009年以来有所恶化;燃料油、焦炭和煤炭是造成北京市大气污染的前3位能源,天然气是最清洁的能源;同种能源与不同污染物的关联程度相似;同种能源与污染物在不同时间段的关联序基本不变,不同能源因子分别表现出"缓慢上升"、"逐渐升高"、"水平S"型和"倒U"型4种态势;燃料油与大气污染物"同增同减",大气污染物与燃料油正相关;天然气与大气污染物"此涨彼消",天然气与大气污染物负相关。     

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.     

Modelling vegetation greenness responses to climate variability in a Mediterranean terrestrial ecosystem

Accurate knowledge of the quality and environmental impact of the highway runoff in Pear River Delta, South China is required to assess this important non-point pollution source. This paper presents the quality characterization and environmental impact assessment of rainfall runoff from highways in urban and rural area of Guangzhou, the largest city of Pear River Delta over 1 year’s investigation. Multiple regression and Pearson correlation analysis were used to determine influence of the rainfall characteristics on water quality and correlations among the constituents in highway runoff. The results and analysis indicates that the runoff water is nearly neutral with low biodegradability. Oil and grease (O&G), suspended solids (SS) and heavy metals are the dominant pollutants in contrast to the low level of nutrient constituents in runoff. Quality of highway runoff at rural site is better than that of at urban site for most constituents. Depth and antecedent dry period are the main rainfall factors influencing quality of highway runoff. The correlation patterns among constituents in highway runoff at urban site are consistent with their dominant phases in water. Strong correlations (r ≥ 0.80) are found among chemical oxygen demand (COD), total phosphorus, Cu and Zn as well as conductivity, nitrate nitrogen and total nitrogen. O&G, COD, SS and Pb in highway runoff at urban site substantially exceed their concentrations in receiving water of Pear River. The soil directly discharged by highway runoff at rural site has contaminated seriously by heavy metals in surface layer accompanying with pH conversion from original acidic to alkaline at present.     

Air Quality Monitoring and Management in Lisbon

The environmental decision-making process is related with the interpretation of data both in spatial and temporal dimensions. This paper presents a methodology that integrates the time-space framework of air quality data to infer the temporal pattern and spatial variability that could be interpreted for environmental decision purposes. Variograms that accommodate time and space lags were used for the analysis and proved to be effective. Its environmental meaning, in particular its relationship with traffic patterns is discussed. Data from air quality monitoring stations located in the central part of Lisbon were used in this study. It describes a strategy to identify the type of vehicles responsible for certain pollutant levels, particularly for nitrogen oxides, and discusses the application of new air quality European legislation to the city of Lisbon, Portugal.