水污染物排放总量分配问题的探讨

水质功能区内水污染物允许排放量和减量指标的确定,以及向有关排污单位进行分配,是实施排污许可证制度的核心,本文采取容量总量控制与目标总量控制相结合,总量控制与浓度控制相结合,公平分配,承认行业差异,承认历史,水体自净容量合理利用等原则,以技术先进性、管理和经济可行性相统一为出发点,对水质功能区内水污染物允许负荷量,排污源允许排污量的分配问题进行探讨。     

SO2排放指标分配方法研究及在我国的实践

SO₂排放指标的合理分配是实施总量控制、排污许可证制度和排污权交易的重要基础.通过对环境质量反演法、历史数据法、排放绩效法和拍卖法等排污指标分配方法优缺点和适用条件的研究,得出基于排放绩效的分配方法较为适用于电力行业,并在江苏省电力行业中进行了成功实践.      

区域水污染物排放总量分配方法研究

污染物允许排放总量分配是水污染总量控制的重要内容 ,分配的合理与否将会直接影响到水污染控制工作的成效。本研究基于经济、社会和环境系统诸要素影响 ,设计了一种定性与定量相结合描述判断矩阵的多指标决策的层次分析法来进行排污总量分摊问题的研究。结果表明 ,该方法既克服了等比例分配方法的不公平性 ,又兼顾了各分区间的差异     

基于公平原则的海域—流域水污染物总量分配方法研究

陆地和海洋是相互影响、相互制约的生态系统,海洋水污染物总量控制目标的实现取决于陆域排污情况,而陆域排污分配要充分考虑其对海洋环境的影响。本文从"海陆统筹"的环境管理角度,基于公平原则,充分考虑海域和陆域之间的相互影响及分配区域的现状情况,给出了"海域-流域-行政区"链条式的水污染物总量控制思路和"初次分配-公平性评估-优化调整再分配"的水污染物总量分配方法。分配过程采用了层次分析法、熵值法、基尼系数法等经典的公平方法,并在辽东湾-辽河流域COD总量分配中予以应用,可为有效治理海洋环境污染问题提供借鉴。     

水环境容量与总量控制在制定排放标准中的应用

针对湖北省府河流域含盐废水大量排放,造成引用水源和农业灌溉水源严重污染的状况,从制定府河流域氯化物排放标准的指导思想出发,研究了府河氯化物的水环境容量在制定排放标准和排污总量控制中的作用,指出污染物的水环境容量研究是进行流域排污总量控制和制定流域排放标准的基础。而执行流域污染物排放标准可有效地实施污染物总量控制,减少对水环境的污染。     

无顺市水污染物总量分配探讨

根据抚顺市地表水系和水域功能区划的分布情况，采用了定额达标分配、治理费用最小，及按现有排污总量进行达标分配的方法对水污染物进行总量分配，从而对减少污染物排放，控制水体污染提供了技术支持。     

基于基尼系数的湖泊流域分区水污染物总量分配

从经济、社会和环境系统整体效益出发,将环境基尼系数应用于总量控制分配中,分别以人口和工业增加值等作为湖泊流域内基尼系数分配的指标,建立了一种定性与定量相结合描述湖泊流域分区水污染物排放总量分配的层次结构模型.该模型综合考虑了各项评价指标,以区域允许排污总量为基础,依据环境基尼系数调整各分区允许排污量的权重比,并依此比例在各分区间进行排污总量分配.同时,以汤逊湖流域为例,根据流域内经济、社会和环境系统的实际特点,以工业增加值为主要限制指标,调整分配方案,计算出该流域水污染物排放总量的分配结果.结果表明,本研究提出的分配方法,克服了等比例分配的不公平性,同时又兼顾了各分区间的实际差异,是一种较好的分配方法.     

美国加州南海岸区域清洁空气激励市场项目概况及进展

目前中国一些地区正在试点探索实施区域性排污交易项目。美国是世界上最早将排污交易理论付诸实践的国家,作为该国最早的区域性大气污染物排污交易计划之一,加州"区域清洁空气激励市场"项目自1994年开始运行。这一排污交易项目不仅实现了氮氧化物与硫氧化物减排目标,而且形成了相对健全的排污交易规则。"区域清洁空气激励市场"的总量控制机制、初始分配和交易规则与排污交易市场运行经验,对中国地方性排污交易项目设计具有重要的借鉴意义。     

嫩江水污染物排放总量分配方法研究

本文针对嫩江沿岸采用氧化塘处理污水和特点，为充分合理利用水环境容量，以流域总量控制的原则为指导，建立了水污染物总量分配模型，预测不同流量和不同排污情况下的水质，确定不同流量下给定水质目标的临界距离和允许排污量。     

水污染物总量分配原则和方法探讨

总量控制污染物排放量和削减量指标的确定并向有关排污单位进行分配,是实行排污许可证制度的核心内容.对这一课题,国内第一批实行排污许可证制度的试点城市,都在进行研究和实验,做法也各不相同.本文介绍丹东市在排污许可证试点工作中,以技术先进性和管理可行性相统一为出发点,经过探讨研究和实施的水污染物总量分配方法,并试图论述其科学合理性、公平合法性和经济可行性.一、区域水污染物总量分配的依据1.规划的区域水环境功能区水质目标.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen (T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks (ANNs) and support vector machines (SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination (R²), Nash–Sutcliff efficiency (NSE), relative efficiency criteria (d_rel). Additionally, Latin-Hypercube one-factor-at-a-time (LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage. However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Field survey of a sustainable sanitation system in a residential house

Sustainable sanitation is an approach for more ecological and sustainable water resources management. In this paper, we proposed one of the new integrated waste treatment systems： an ＂sustainable sanitation system＂ that includes separation of the black water from water system by a non-flushing toilet （bio-toilet）, and a gray water treatment based on a biological and ecological concept. Sustainable sanitation system also converts the domestic waste to soil conditioners and fertilizers, for farmland use. As one of the case studies, Environmentally Symbiotic Housing in which people actually live using the bio-toilet for the black water treatment and the household wastewater treatment facility for the gray water was introduced. The availability of this system was investigated by analyzing the sawdust used in the bio-toilet and the quality of the effluent in the household wastewater treatment facility. As the result, the water content of the sawdust did not exceed 60% in any of the sampling points and the BOD and COD of the effluent of the household wastewater treatment facility were below 10 and 20 mg/L respectively, due to the low loading. Compared to the pollution load on the water environment created by the conventional system, it was found that the effluent of the house has a lower load than the tertiary treatment and the volume of the water consumption is 75% of the conventional system.     

累积流量模型在河流水质管理规划中的应用

借助混合率与保存率的概念,将累积流量模型应用到河流水质管理规划中,提出了一个新的可考虑向扩影响的规划模型,并将水质管理目标定在取水口水质达标上。     

基于水质目标管理的河流治理方案制定方法及其案例研究

针对我国河流污染程度高,污染类型复杂的现状,实施水质目标管理是河流治理的根本选择.我国在水污染总量控制的研究起步比较早,但缺少基于水质目标的治理方案编制方法的系统性研究.本文提出了适合于我国国情的基于水质目标的河流治理方案制定方法,基本框架包括水质问题诊断、目标确定与负荷分配、河流治理任务实施和实施效果评估4个基本部分.该方法以河流容量总量控制为基础,突破了传统了目标总量控制方式,并在滏阳河邢台段进行了实际应用.水环境诊断结果显示,氨氮是滏阳河邢台段主要超标污染物.以国控及省控断面为基础,在滏阳河邢台段设定了4个考核断面,设置氨氮小于10、11、12 mg·L-1,COD小于80、55、50 mg·L-1等多个组合目标情景.划定控制单元13个,核算了各控制单元水环境容量和现状负荷,并按等比例分配的原则将需削减负荷分配到排污口.基于负荷分配结果,提出通过重点工业企业和污水处理场治理控制点源污染,通过农村生活污水治理控制面源污染,通过河岸垃圾治理减少河道负荷存量,通过河流湿地建设增加负荷去除能力等一系列治理措施.     

佛山水道引水对环境容量影响研究

采用污染负荷优化分配的线性规划方法,通过感潮河网水环境数学模型模拟得出污染贡献率。求取不同引水方案时佛山水道的环境容量,并建立引水量与环境容量的回归方程。研究结果表明,环境容量与引水量呈线性递增关系。根据回归方程可反推得出引水方案或削污方案,为引水与截污的实施提供了数据支持,并且对佛山水道综合整治的优化决策具有指导意义。     

钢铁行业废水处理中的膜用阻垢剂的研究

介绍钢铁行业用水及排水现状,水质特点,水处理技术的水平,适用于钢铁行业水处理零排放工程的一般预处理及深度反渗透处理工艺,采用这种工艺存在的问题及国内外广泛采用的解决方法。针对中水水质特性、水质结垢特点、阻垢剂机制,研究出一种适用于钢铁行业中水回用的膜用阻垢剂,通过实验室动态试验,结果说明:该药剂具有良好的阻垢分散效果,达到国内外普遍采用的阻垢分散剂的阻垢效果,在钢铁行业废水回用处理中有良好的适用性。     

基于非线性响应函数和蒙特卡洛模拟的滇池流域污染负荷削减情景分析

为定量了解滇池外海水质对流域污染负荷削减率的响应变化程度,并评估相关决策的潜在风险,在长期的水质模拟结果基础之上,本文使用内嵌非线性响应函数的蒙特卡罗模拟方法,在2个不确定性水平下（5%和10%的变异范围）分析滇池外海为达到3个水质目标情景（Ⅲ类、Ⅳ类和Ⅴ类）的污染负荷削减及其不确定性.模型结果表明,在2种不确定性水平...     

厌氧生物滤池-生物接触氧化法治理酿造生产污水工程实例

文章论述利用厌氧生物滤池-生物接触法为主要工艺,治理酿造厂豆制品加工污水,其中COD高达6500mg/L,BOD5高达2500 mg/L.SS高达2600 mg/L.厌氧滤池处理有机废水效果稳定,污染负荷高,抗击负荷能力强,COD去除率高,在80%左右,实际污水经过处理后水质结果表明,该工艺处理的污水达到了排放标准,同时经济合理     

湖泊水库水体氮、磷允许纳污量定量研究

在充分考虑湖库水体污染物实际自净能力、并分析其出流污染物浓度分布规律的基础上,根据风险分析理论和Monte Carlo模拟方法,提出了湖库水体氮、磷允许纳污量计算方法,指出:在满足湖库水体污染物浓度达标率90%以上的条件下,所对应的水体污染物降解量才是湖泊水库水体氮、磷允许纳污量.通过实际算例对水库总氮、总磷允许纳污量的计算,说明了所提出的计算方法的适用性.