Prediction of Leachate Level in Kimpo Metropolitan Landfill Site by Total Water Balance

Kimpo metropolitan landfill has received various kinds of wastessince January 1992. The leachate level was measured to be 10.3 m in May 1995 and the level increased to 12.2 m in August 1996. Therefore, to prove the reason for the increasing leachate level, we calibrated hydraulic conductivity of each waste andintermediate layer using the HELP (Hydrologic Evaluation ofLandfill Performance) model. The leachate generation data measured from February 1993 to October 1995 was used in the model calibration. As a result of a model calibration, we obtained anaverage infiltration ratio and used this in analysis of the total water balance to predict elevation of leachate level. Main causes of the elevation of the leachate level were the high water content of the waste and the degradation of the leachate-drainage system caused by the subsidence of a naturalbarrier layer.     

Modeling of non-point source pollution in a Mediterranean drainage basin

SWAT ver. 2000 was used to predict hydrographs, and sediment, nitrate and total phosphorus loadings from a 1349 km² mountainous/agricultural watershed in Northern Greece. The model was calibrated and verified using continuous meteorological data from eight stations within the drainage area, and runoff, sediment and nutrient concentrations measured at nine stations located within the main tributaries of the watershed, for the time period from May 1st, 1998 to January 31st, 2000. Model validation methodology and resulting input parameters appropriate for Mediterranean drainage basins are presented. Predicted by the model hydrographs, sedimentographs and pollutographs are plotted against observed values and show good agreement. Model performance is evaluated using the root mean square error computation and scattergrams of predicted versus observed data. The validated model is also used to test the effectiveness of three alternative cropping scenarios in reducing nutrient loadings from the agricultural part of the watershed. The study showed that this model, if properly validated, can be used effectively in testing management scenarios in Mediterranean drainage basins.     

甲硫醚废气制取二甲基亚砜技术研究

选择双氧水作氧化剂，将具有恶臭气味的涕灭威生产的副产物甲硫醚氧化成无臭的二甲基亚砜。通过实验，优化了工艺条件，减少了安全隐患，提高了二甲基亚砜的产率，消除了恶臭污染。     

经口摄入土壤多溴联苯醚生物可给性变化及影响因素的体外消化模拟

误食土壤是污染物(如多溴联苯醚)人体(主要是儿童)暴露的重要途径,人体消化道内污染物吸收的生物可给性是针对此种暴露方式进行定量风险评估的有效途径之一.本研究采用体外消化实验模拟3种不同有机碳含量的天然土壤中典型多溴联苯醚(BDE-28、BDE-47、BDE-99和BDE-153)在胃和小肠消化液中的释放,验证部分消化释放的多溴联苯醚因消化残留固相表面的再吸附造成低估实际生物可给性,并通过不同水土比的拟合计算予以校正.结果表明,校正后的消化率普遍高于校正前;就不同土样而言,BDE-28、BDE-47、BDE-99和BDE-153在不同初始暴露浓度条件下平均提升比例范围分别为14.3%~42.3%、11.1%~32.1%、4.9%~12.3%和0.0%~7.7%.因此,未经校正的消化率会显著低估PBDEs消化道内的生物可给性,尤其是低溴代组分及PBDEs初始浓度较高或高TOC含量的土样.校正后BDE-28、BDE-47、BDE-99和BDE-153的消化率分别维持在21.9%~54.7%、18.8%~43.1%、13.4%~27.2%和9.3%~19.9%.此外,PBDEs的消化率与其辛醇-水分配系数的对数lg KOW呈显著负相关;而与土壤TOC含量及PBDEs初始暴露浓度的相关性并不显著,尤其是高溴代组分.     

ASM1耦合曝气模型对污水处理厂的模拟研究

为了更好地模拟污水处理厂实际的曝气方式及溶解氧浓度,采用更加精确的曝气模型对某污水处理厂进行了模拟研究.该模型考虑了污泥浓度、堵塞及温度等因素对氧传质的影响,并将该曝气模型与ASM1相耦合.首先,通过灵敏度分析确定了对该污水处理厂出水指标影响较大的参数,分别为异养菌产率系数YH、异养菌最大比增长速率μH、自养菌最大比增长速率μA及自养菌氧利用半饱和系数KOA.然后,测定部分灵敏度较高的参数并使用测量结果对模型进行校正,校正结果使用希尔系数表征.最后,使用另一批数据对校正参数进行验证.模拟的COD、氨氮、总氮和好氧池末端溶解氧的希尔不等系数分别是0.13、0.23、0.20和0.15,而通过控制溶解氧浓度或理论氧转移效率模型模拟则出现氨氮、溶解氧、总氮及COD的希尔不等系数不同程度上升的结果.校验后的ASM1/曝气耦合模型参数可以很好地应用于污水处理厂的模拟当中,对于优化污水厂曝气控制具有重要意义.     

校准曲线的制作及有关问题的探讨

详细阐述了校准曲线的制作方法;校准曲线的空白试验、相关系数、截距、斜率、线性范围的要求和影响因素;标准曲线与工作曲线的区别;校准曲线应用中的注意事项;同时收集了21个常规分析项目的空白吸光度和标准曲线斜率的范围,用于分析中的质量控制,具有较好的参考价值。     

ASTAR IR-200红外三波数测油仪自校方法

针对ASTAR IR-200红外三波数测油仪,提出仪器的自校方法。     

基于GLUE法的多指标水质模型参数率定方法

目前对水质模型进行参数率定通常利用计算机算法来实现,但由于水质模型日趋复杂的非线性结构往往会导致"异参同效"现象,无法通过单个似然度判断参数的取值是否能够取得真值.为避免这一情况,本文提出了一套基于GLUE法的多目标模型参数率定方法,并以WASP水质模型的应用为例,通过Sobol方法确定模型的敏感参数,并利用DO、CBOD、氨氮、硝态氮4项指标的似然函数对参数同时进行率定.结果表明,该方法既可以有效地避免因追求"过拟合"而造成模型参数取值不当,也可以减小模型参数的不确定性,为具有"异参同效"现象的复杂模型的参数率定工作提供了一个更为可靠的方法.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.