电渗析在丙烯酸丁酯废水预处理中的应用

采用电渗析法预处理丙烯酸丁酯生产废水,可将废水中的有机酸盐浓缩回收,同时大大降低废水的污染物浓度.重点研究了淡水浓水初始体积比的影响,同时考察了电渗析过程中水的迁移.实验确定了淡水浓水的最佳初始体积比为5∶1,此时对COD为61 650 mg/L的废水,COD去除率可达99.5%,脱盐率在99.5%以上,同时可将废水的...     

曝气强度对同时硝化反硝化（SND）脱氮过程中N2O排放的影响

为了控制污水脱氮中N2O排放,在不同曝气强度下研究了好氧硝化段同时硝化反硝化（SND）系统的N2O排放特性,并采用PCR—DGGE技术分析微生物群落特征。结果发现,随着曝气强度的增强,系统总氮去除率下降,但脱氮中N2O—N所占比例则上升,实验中从低到高3个曝气强度下,总氮去除率分别为80．01％、65．28％和58．62％,脱氮中N2O—N所占的比例为1．89％、7．84％和9．20％。PCR—DGGE分析显示,和低曝气强度下相比中、高曝气强度下系统微生物群落发生明显变化,但中曝气强度和高曝气强度下系统微生物群落表现出较高相似性。这表明,不同曝气强度下系统N2O排放受到氮素转化和微生物群落变化的影响。适宜曝气强度不仅提高总氮去除率,还可有效控制N2O排放。     

300MW燃煤锅炉机组超细颗粒聚并器的实验研究

为了解决燃煤锅炉烟气中超细颗粒难以脱除的问题,基于流体动力学原理设计了一种超细颗粒聚并器,并在300 MW燃煤锅炉机组电除尘器的前置烟道中进行了实验研究。结果表明,聚并器内部存在超细颗粒之间以及超细颗粒与大颗粒之间的相互聚集行为,从而使超细颗粒数量显著减少。例如,对于粒径在2.65和10.48μm以下的颗粒,其体积比例在聚并器出口分别减少了56.7%和62.3%,在电除尘器出口的粉尘浓度减少了26.34 mg/Nm3,这表明,基于流体动力学原理的聚并器对超细颗粒的聚并作用明显,具有良好的应用前景。     

丙烯腈生产废水中聚合物的资源化利用

以丙烯腈生产废水中的丙烯腈低聚物为原料制备聚丙烯酰胺。通过正交实验考察了水解反应条件和交联反应条件对反应的影响。FTIR表征结果显示,丙烯腈低聚物中的氰基已完全水解为酰胺基,产物聚丙烯酰胺中含有酰胺基和羧基。实验结果表明,在自来水加入量100 m L、水解反应温度95℃、m(Na OH)∶m(丙烯腈低聚物)=2.0、水解反应时间3 h的最佳水解反应条件,交联反应温度60℃、质量分数37%~40%的甲醛加入量6 m L、交联反应时间2 h的最佳交联反应条件下,处理20 g丙烯腈低聚物,可得到产物聚丙烯酰胺14.50 g,聚丙烯酰胺的水解度为21.1%、相对分子质量为2.7×106。产品性能满足Q/SH 0046—2007《钻井液用聚丙烯酰胺技术要求》中部分水解聚丙烯酰胺的性能要求。     

Geochemistry of tin (Sn) in Chinese coals

Environmental Geochemistry and Health - Based on 1625 data collected from the published literature, the geochemistry of tin (Sn) in Chinese coals, including the abundance, distribution, modes of...     

A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007

This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O₃ concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA's AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O₃ concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2 ppb was 4.2 ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50 ppb. In fact the model tends to under-predict when concentrations exceed 70 ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0 ppb (Normalized Mean Error (NME) = 20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

南山铁矿风场及扩散规律风洞模拟研究

以风洞模拟方式研究中性层结条件下南山铁矿凹山采场地域边界层风场特征,并以示踪气体扩散摸拟方法给出该地域大气扩散参数的实验结果。