桂西北河池地区耕地变化及其驱动力Logistic回归分析

桂西北河池地区土地退化严重,耕地少,区域农业发展受限。基于TM遥感图像、DEM等空间数据并结合社会经济统计数据,利用空间分析方法及Logistic回归分析模型,定量分析了1952～2006年桂西北河池地区11个县耕地的时空动态变化规律及其驱动机制。研究结果表明：1952～2006年河池地区耕地总量的变化经历了迅速增加-波动变化-迅速减少-缓慢减少的过程,空间上变化率不均衡,且近20多a间西部地区耕地减少迅速,其变化体现了国家政策的主导驱动作用;根据回归结果提取出7类影响耕地分布的主要解释变量,其中海拔和人口分布为耕地空间分布格局分异的关键影响因素,其次是坡度Ⅰ(0°～5°)、GDP、至主要公路距离、至主要河流距离和至主要城镇距离;不同县之间耕地变化驱动力的解释变量存在差异,且各县耕地分布概率对于海拔、坡度Ⅰ(0°～5°)、GDP这3类解释变量较敏感,而其他解释变量敏感程度较低;东部地区耕地分布的概率更大.     

Modeling potential herbicide loss to surface waters on the Swiss plateau

Lack of sufficiently detailed data often limits the applicability of complex transport-reaction models for estimating potential herbicide loss to surface waters. Therefore, there is also a need for simple models that are easy to apply but still capture the main features of the underlying processes.In this study, a simple regression model was developed to assess the vulnerability of catchments in the Swiss Plateau to diffuse herbicide loss to surface waters. The model is designed as a screening tool to rank the catchments in a relative sense and not to calculate Predicted Environmental Concentrations (PEC) of pesticides. The main goal is to capture two dominating factors controlling diffuse herbicide transport into streams and rivers. These factors are herbicide application and fast flow processes that are mainly responsible for herbicide transport. In a first step vulnerability of sites to herbicide loss is estimated based on site-specific conditions irrespective of actual herbicide application. In the second step, this vulnerability assessment is combined with actual herbicide application data to estimate the potential herbicide loss.The fast flow index (FFI), derived from discharge data using a base flow separation method, was applied as a proxy for the amount of fast flow occurring. The influence of catchment attributes (including topographic, climatic and soil data) on the FFI was analyzed using a multiple regression approach based on data from 57 catchments of the Swiss Plateau. By combining regression analysis with mechanistic knowledge, a two factor non-linear model based on river density and soil permeability as dominant input factors was selected as the best model for FFI prediction given the available data. Higher dimensional models had to be excluded because the strong correlation between the potential input factors led to unrealistic dependences while only minimally improving the quality of the fit.The spatial pattern of the predicted FFI as a measure for the vulnerability to diffuse herbicide losses shows a clearly increasing trend from the western to the eastern part of the Swiss Plateau and towards the pre-alpine/alpine regions in the south.In general the pattern of herbicide use corresponds to site conditions typical of a low FFI. However, the spatial analysis revealed exceptions, namely areas in which high actual herbicide use coincides with a high FFI.Despite the uncertainties in the model, this simple approach seems to be useful for supporting site-adapted agricultural practice whenever the higher accuracy of more detailed models is not required or too expensive to achieve. In addition, in combination with data on actual herbicide application, it can support the design of monitoring strategies by identifying critical areas of actual herbicide loss.     

A statistical analysis of the carbon dioxide capture process

Post combustion carbon dioxide (CO₂) capture is one of the most commonly adopted technologies for reducing industrial CO₂ emissions, which is now an important goal given the widespread concern over global warming. Research on amine-based CO₂ capture has mainly focused on improving effectiveness and efficiency of the CO₂ capture process. Our research work focuses on studying the relationships among the significant parameters influencing CO₂ production because an enhanced understanding of the intricate relationships among the parameters involved in the process is critical for improving efficiency of the CO₂ capture process. This paper presents a statistical study that explores the relationships among parameters involved in the amine-based post combustion CO₂ capture process at the International Centre for CO₂ Capture (ITC) located in Regina, Saskatchewan of Canada. A multiple regression technique has been applied for analysis of data collected at the CO₂ capture pilot plant at ITC. The parameters have been carefully selected to avoid issues of multicollinearity, and four mathematical models among the key parameters identified have been developed. The models have been tested, and accuracy of the models is found to be satisfactory. The models developed in this study describe part of the CO₂ capture process and can help to predict performance of the CO₂ capture process at ITC under different conditions. Some results from a preliminary validation process will also be presented.     

Oil spill cleanup cost estimation—Developing a mathematical model for marine environment

The field of oil spill cost modelling is not as well explored as desirable. Generally speaking, the existing models have either low accuracy, in that their predictions are far from the real cost, or low applicability, in that they are only valid under very specific conditions; such as in one particular country. This work strives to construct a model that is functional in a global scope and still possess a high level of accuracy. The resulting attempt is in many ways superior to the publicly available competitors, not only because of its predictive capacity but also because the model is quick to use, and its input variables should be readily available to any informed user. The model is more accurate comparing with similar available models. However, further study is needed to modify it to obtain more realistic results.     

Statistical Analysis of Air Pollutants and Meteorological Parameters in Afyon, Turkey

In this study, the relation between sulfur dioxide (SO₂) and particulate matter (PM) concentrations periodically measured in the city of Afyon’s atmosphere with meteorological factors such as precipitation, humidity, temperature, wind velocity, and inversion were investigated. The mean values of SO₂ and PM concentrations measured during the winter months of October–March 1990–1999 were correlated with the meteorological parameters of the same period. Simple and multiple linear regression analysis were utilized to evaluate the contribution of meteorological variables. The statistical results show that the pollutants, i.e., SO₂ and PM are dependent upon humidity, temperature, and inversion at the 1% significance level; while the dependence of both pollutants with temperature is negative when those of humidity and inversion are positive. Two models in which temperature and inversion are dependent with multiple variables are recommended for predicting the contribution of meteorological parameters on SO₂ and PM. In addition, the relationship between humidity, temperature, and inversion with pollutants is also determined using nonlinear (polynomial) models.     

Optimal Selection of Priority Development Areas Considering Tradeoffs Between Hydrology and Development Configuration

Mixed-integer linear programs are proposed for siting development and conservation areas in watersheds, addressing economic objectives (development perimeter and proximity) and ecological objectives. Links between watershed hydrology and ecology need not be well defined. Parameters for the linear programs are obtained from linearization of the SWAT hydrologic model.     

Nutrient dynamics between sediment and overlying water in the inner part of Izmir Bay, Eastern Aegean

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0–20, 20–63, 63–2,000 μ) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.     

基于主成分分析-多元线性回归的松花江水体中多环芳烃源解析

对松花江全流域14个监测断面的16种美国环保局优先控制的多环芳烃(PAHs)的主要来源及其贡献率应用主成分因子分析-多元线性回归模型(PCA-MLR)进行了来源解析。结果表明:松花江全流域为化石和石油燃料的复合PAHs污染,水体环境中PAHs首要污染源为化石燃料燃烧和交通污染,合计贡献率为63.1%,第二大污染源为工业和民用燃煤污染,合计贡献率为36.9%,沿江的石化、石油基地、大型焦化厂、电厂都是PAHs的主要来源。     

Distribution of Polycyclic Aromatic Hydrocarbons (PAHs) and phenolic endocrine disrupting chemicals in South and Southeast Asian mussels

A comprehensive monitoring survey for polycyclic aromatic hydrocarbons (PAHs) and phenolic endocrine disrupting chemicals (EDCs) utilizing mussels as sentinel organisms was conducted in South and Southeast Asia as a part of the Asian Mussel Watch project. Green mussel (Perna viridis) samples collected from a total of 48 locations in India, Indonesia, Singapore, Malaysia, Thailand, Cambodia, Vietnam, and the Philippines during 1994–1999 were analyzed for PAHs, EDCs including nonylphenol (NP), octylphenol (OP) and bisphenol A (BPA), and linear alkylbenzenes (LABs) as molecular markers for sewage. Concentrations of NP ranged from 18 to 643 ng/g-dry tissue. The highest levels of NP in Malaysia, Singapore, the Philippines, and Indonesia were comparable to those observed in Tokyo Bay. Elevated concentrations of EDCs were not observed in Vietnam and Cambodia, probably due to the lower extent of industrialization in these regions. No consistent relationship between concentrations of phenolic EDCs and LABs were found, suggesting that sewage is not a major source of EDCs. Concentrations of PAHs ranged from 11 to 1,133 ng/g-dry, which were categorized as “low to moderate” levels of pollution. The ratio of methylphenanthrenes to phenanthrene (MP/P ratio) was >1.0 in 20 out of 25 locations, indicating extensive input of petrogenic PAHs. This study provides a bench-mark for data on the distribution of anthropogenic contaminants in this region, which is essential in evaluating temporal and spatial variation and effect of future regulatory measures.     

Determination of Nitrobenzene in Wastewater Using a Hanging Mercury Drop Electrode

The determination of trace amount nitrobenzene in wastewater on a hanging mercury drop electrode was studied. The determination conditions of pH, supporting electrolyte, accumulation potential, accumulation time, and voltammetric response were optimized. The sharp peak of the nitrobenzene was appeared at 0.05 V. The peak electric current was proportional to the concentration of nitrobenzene in the range of 1.47 × 10⁻⁵ ∼ 1.0 × 10⁻³ mol/l with relative standard deviations of 3.99 ∼ 8.94%. The detection limit of the nitrobenzene in water was 5 × 10⁻⁶ mol/l. The proposed method offered low limit of determination, easy operation, the use of simple instrumentation, high sensitivity and good reproducibility. It was applied to the determination of nitrobenzene in wastewater with an average recovery of 94.0% ∼ 105%. The proposed method provided fast, sensitive and sometimes real time detection of nitrobenzene.