北京市开展区域水环境合作探究

通过分析北京市地表水资源、水环境质量现状及存在的问题,得出生态环境用水严重短缺是制约北京市水环境质量全面改善的根本原因,并对此提出全面加强区域水环境合作、改善北京市水环境的基本思路,及与周边地区开展水环境合作的途径及建议。     

河北省地表水环境污染特征及分析

河北省1998年-2005年的水环境质量监测数据分析表明：河北省地表水污染恶化趋势基本得到遏制,但部分地区水污染矛盾仍很突出;水体总体污染减轻,但氨氮污染有加重趋势;主要湖（库）水水质稳定,但普遍呈不同程度的富营养化。在此基础上,分析了地表水污染的原因,并提出了河北省改善地表水环境污染的对策与措施。     

环保新思维：绿色保险

我国现在正处于环境事故高发期,而环境污染损害赔偿是企业,甚至是国家必须面对的现实问题。然而单凭企业承担责任是力所不能及的,最终不得不由国家买单,给国家带来沉重的负担。这种情况迫切需要建立环境污染损害责任保险机制,即绿色保险,把赔偿引向社会化。保险本身就是一种救灾形式,因为它能分散风险,减少损失。针对我国的具体情况,建立适宜的环境污染责任保险模式才能平衡发展与环境保护的关系、在全社会牢固树立生态文明理念。     

污染防治设施社会化运营模式及其对区域环境与经济协调发展的影响

针对城市化进程加快引发的一系列环境污染问题,指出了加快污染防治设施社会化运营的必要性,并从污染治理设施的种类、污染治理设施的社会化运营分析和运作模式三方面论述了如何进行污染治理设施的社会化运营,从经济发展、污染防治设施运行、引入竞争机制等方面概述了污染防治设施社会化运营对区域环境与经济协调发展的影响。     

Development and Use of a Sedimentation Risk Index for Unpaved Road‐Stream Crossings in the Choctawhatchee Watershed1

Abstract: Unpaved road‐stream crossings increase sediment yields in streams and alter channel morphology and stability. Before restoration and sedimentation reduction strategies can be implemented, a priority listing of unpaved road‐stream crossings must be created. The objectives of this study were to develop a sedimentation risk index (SRI) for unpaved road‐stream crossings and to prioritize 125 sites in the Choctawhatchee watershed (southeastern Alabama) using this model. Field surveys involved qualitative and quantitative observations of 73 metrics related to waterway conditions, crossing structures, road approaches, and roadside soil erosion. The road‐stream crossing risk analyses involved elimination of candidate metrics based on redundancy, skewness, lack of data, professional judgment, lack of nonzero values, unbalanced box plots, and limited ranges of values. A final selection of 12 metrics formed the SRI and weighed factors involving soil erodibility, road sedimentation abatement features, and stream morphology alteration. The SRI was organized into narrative categories (excellent, good, fair, poor, and very poor) based on the distribution of scores. No excellent sites (scores ≥55) were found in this study, 17 (20.7%) were good (low sedimentation risk), 37 (45.1%) were fair (moderate sedimentation risk), 26 (31.7%) were poor (high sedimentation risk), and two (2.5%) were very poor (high sedimentation risk). There was no significant difference in SRI scores among crossing structure type (round culverts, box culverts, and bridges) (H = 4.31, df = 2, p = 0.058). A future study of the Choctawhatchee watershed involving the same study sites could assess the success of restoration plans and activities based on site score improvement or decline.     

Development of a Quantitative Pasture Phosphorus Management Tool Using the SWAT Model1

Abstract: Assessment tools to evaluate phosphorus loss from agricultural lands allow conservation planners to evaluate the impact of management decisions on water quality. Available tools to predict phosphorus loss from agricultural fields are either: (1) qualitative indices with limited applicability to address offsite water quality standards, or (2) models which are prohibitively complex for application by most conservation planners. The purpose of this research was to develop a simple interface for a comprehensive hydrologic/water quality model to allow its usage by farmers and conservation planners. The Pasture Phosphorus Management (PPM) Calculator was developed to predict average annual phosphorus (P) losses from pastures under a variety of field conditions and management options. PPM Calculator is a vastly simplified interface for the Soil and Water Assessment Tool (SWAT) model that requires no knowledge of SWAT by the user. PPM Calculator was validated using 33 months of data on four pasture fields in northwestern Arkansas. This tool has been extensively applied in the Lake Eucha/Spavinaw Basin in northeastern Oklahoma and northwestern Arkansas. PPM Calculator allows conservation planners to take advantage of the predictive capacity of a comprehensive hydrologic water quality model typically reserved for use by hydrologists and engineers. This research demonstrates the applicability of existing water quality models in the development of user friendly P management tools.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

煤粉锅炉飞灰份额影响因素分析

通过对10个电厂22台机组36组实测数据的分析,论述了燃煤挥发分、灰分及过剩空气系数对煤粉锅炉飞灰份额的影响趋势。     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

江河水源地突发性水污染事故风险评价

近年来,我国江河饮用水水源地突发性水质污染事故频发,成为我国面临的最严重的环境问题之一.江河水源地突发性水质污染事件的风险评价是确保饮用水源地水质安全的重要手段,对突发性水质污染事故,采取适当的应急处理措施.