Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.     

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.     

绿色大学环境能源优化研究

绿色大学是在日益严重的环境问题背景下生态文明和社会可持续发展理念融合于校园的必然趋势.作为技术传承和创新的主体,积极探索和深化高校能源改革具有非常重要的意义.本文以中国石油大学的面板数据作为数据研究基础,结合气候能源因素,提出基于综合节能模型的绿色大学构想,采用簇聚类和遗传优化进行能源整合,动态评估后进行系统参数加权优化,从而达到能源优化使用的目标.实践表明,该模型有效提升能源效率和改善环境,具有重要的应用意义.     

浙江省"十二五"城市声环境监测点位优化调整研究

随着城市建设步伐的加快,人口数量增多,城市基础设施的完善,建成区的扩大和功能区类型的改变,"十二五"城市声环境监测点位的调整、优化是必然趋势.本文结合浙江省"十二五"城市声环境监测点位优化布设的实际工作情况,对城市声环境监测点位优化布点原则、方法等进行了阐述.以"十一五"声环境监测点位布设现状为基础,结合功能区环境噪声的普查数据,对优化选点监测数据进行分析,选出具有空间分布适当,可以保证设备安全,方便操作,并且数据具有较好的代表性的测点.优化调整后,城市区域环境噪声有效网格覆盖面积增加了80.8%,道路交通噪声监测总路长增加了67.0%,功能区定点噪声测点数量增加了129.2%,优化调整后的监测点位更能客观反映城市区域环境噪声实际情况.     

基于修正A值法估算西安市大气环境容量研究

采用以单箱模型法为基础的A值法对西安市大气容量进行估算,并将干沉降、湿沉降和化学转化三个消除过程引入模型测算中,借鉴国内外对于大气常规污染物的清除系数的科学研究成果,对研究区域的SO2、NO2、PM10及PM2.5等4项常规污染物的环境容量进行估算。结果表明,执行2012年新的环境质量标准下,西安市SO2、NO2、PM10及PM2.5大气环境容量分别为13.86×104吨/年,9.24×104吨/年、1.62×105吨/年及8.09×104吨/年。     

水资源规划优化技术研究进展及展望

针对水资源管理与规划的发展过程,详细论述了水资源系统管理与规划中常用优化技术的国内外研究成果及应用.根据是否考虑了模型参数或者模型结构的不确定性问题,将优化模型分为确定性优化模型和不确定性优化模型,通过对不确定性优化模型的介绍指出了不确定性优化是当前水资源系统优化的热点,同时指出未来不确定性优化技术发展方向等.     

液化石油气火灾爆炸环境风险后果影响分析研究

研究以液化石油气火灾/爆炸事故为对象,通过TNT当量系数法和BLEVE火球热辐射模型法计算分析,结果表明：（1）火灾爆炸事故的危害后果一般随距离增加而降低;（2）沸腾液体扩展蒸汽云爆炸（BLEVE）的事故后果比蒸汽云爆炸（VCE）严重;（3）危险物质泄漏引发的火灾爆炸事故的环境风险后果计算可以采用这两种方法,同时其计算结果能为环境突发事件应急管理和决策提供基础数据.     

多目标优化方法在区域水资源优化配置中的应用——以唐山市为例

水资源供需矛盾日益加剧,如何优化配置区域内有限的水资源已成为水资源规划与管理研究中的热点.本文在考虑不同水质和水源的基础上,研究了决策变量的约束条件,综合考虑不同用水户的用水效益,采用工业、生活、环境和农业多目标优化的方法,按照决策者的不同意愿,给出不同的配置方案,即一系列非劣解集.通过调用Matlab优化工具箱中的函数对其进行求解,给出了5种不同的水资源优化配置方案,能够合理配置唐山市区内有限的水资源,使得该区域内环境、社会与经济协调发展.     

Characterization of primary precipitate composition formed during co-removal of Cr(VI) with Cu(II) in synthetic wastewater

BACKGROUND, AIMS AND SCOPE: Hexavalent chromium [Cr(VI)] cannot react with either carbonate or hydroxide to form chromium precipitates. However, by using a precipitation technology to treat plating wastewater containing Cr(VI), Cu(II), Ni(II) and Zn(II), approximately 78% of Cr(VI) (initial 60 mg/L) was co-removed with the precipitation of Cu(II), Ni(II) and Zn(II) (each 150 mg/L) by dosing with Na2CO3 (Sun 2003). Direct precipitation by forming Cu(II)-Cr(VI) precipitates followed by adsorption of Cr(VI) onto freshly formed Cu-precipitates was subsequently found to be the main mechanism(s) involved in Cr(VI) co-removal with Cu(II) precipitation by dosing Na2CO3 stepwise to various pH values (Sun et al. 2003). This study was. carried out to further characterize the formation of primary precipitates during the early stages of copper precipitation and simultaneous removal of Cr(VI) with Cu(II). METHODS: Test metal-solutions were prepared with industrial grade chemicals: CuCl2 x 2H2O, Na2SO4 and K2Cr2207. NaCO3 was added drop-wise to synthetic metal-solution to progressively increase pH. For each pH increment, removal of soluble metals was detected by atomic absorption spectrophotometer (AAS) and surface morphology of precipitates was analyzed by scanning electron microscope (SEM). To further characterize the formation of primary precipitates, a series of MINEQL+ thermodynamic calculations/analyses and equilibrium calculations/ analyses were conducted. RESULTS AND DISCUSSION: MINEQL+ thermodynamic calculation indicated that, for a system containing 150 mg/L Cu(II) and 60 mg/L Cr(VI) with gradual Na2CO3 dosing, if any precipitates can be formed at pH 5.0 or lower, it should be in the form of CuCrO4. Comparison tests using systems containing the same equivalent of Cu(II) plus Cr(VI) and Cu(II) plus SO4(2-) showed that the precipitation occurred at a pH of around 5.0 in the Cu(II)-Cr(VI) system and around 6.0 in the Cu(II)-SO4(2-) system. The discrepancy of the precipitation was indeed caused by the formation of Cu-Cr precipitates. The initiation of copper removal at pH around 5.0 for the Cu-Cr co-removal test was not attributable to the formation of Cu-CO3 precipitates, instead, it was most likely through the formation of insoluble Cu-Cr precipitates, such as CuCrO4 and CuCrO4 x 2Cu(OH)2. Experimental tests, equilibrium calculations, MINEQL+ thermodynamic calculations and surface morphologies for systems using higher concentrations of Cu(II) and Cr(VI) further verified the most probable composition of primary precipitates is copper-chromate. CONCLUSION: In the Cu-Cr co-removal test with Na2O3 dosing to increase pH and induce metal precipitation, copper-chromate precipitates are the primary precipitates produced and contribute to the initial simultaneous removal of copper and chromium.     

水体中MC-LR的高效液相色谱检测前处理条件优化

通过正交实验设计,对水体中MC-LR前处理过程中SPE柱的选择、水样pH值、洗脱液有机相浓度、酸度和体积等关键因素进行综合分析,得出最优前处理方案。通过精密度和加标回收实验,得出该方法精密度为4.81%,加标回收率为98.96%。