Maximum nitrogen removal in the step-feed activated sludge process.

This paper presents a mathematical framework that can be used to determine the flow distributions for a step-feed activated sludge process that result in maximum nitrogen removal. The model indicates that nitrogen removal efficiency in a step-feed activated sludge process is highly dependent on the ultimate biochemical oxygen demand (BOD(L))-to-total Kjeldahl nitrogen (TKN) ratio of the wastewater. For typical domestic wastewater, which has a relatively high BOD(L)-to-TKN ratio, the step-feed process will outperform the Modified Ludzack-Ettinger process for nitrogen removal, when the flow to each step is optimally distributed. Using plant-specific water quality data and operating conditions from a 1-year period, nitrogen removal performance for four step-feed activated sludge plants operated by the Sanitation Districts of Los Angeles County (California) was calculated using the developed model. The calculated nitrogen removal efficiencies match well with the actual plant performance data. These results validate the model as a useful tool for predicting nitrogen removal in a step-feed activated sludge process. Other analyses revealed that improvements in nitrogen removal at existing facilities are achievable by adjusting the split of primary effluent flow to each anoxic zone several times during the day. The timing of the adjustments and the optimal flow splits can be determined from data on diurnal fluctuations in BOD(L) and TKN concentrations. An example is provided to illustrate the application of such an operating strategy and the potential enhancement of nitrogen removal.     

Quantification of the dissolved organic matter effect on the sorption of hydrophobic organic pollutant: application of an overall mechanistic sorption model

This study presents an overall sorption model to estimate the sorption equilibrium coefficients of hydrophobic organic pollutants for heterogeneous aquatic systems. This proposed model combines a series of sorption equilibrium relationships including the adsorption of dissolved organic matters on particulates, the binding between organic pollutants and dissolved organic matters, and the sorption of organic pollutants on particulates with or without the presence of dissolved organic matters. By using this model, variations among the sorption equilibrium coefficients with the concentrations of dissolved organic matters are obtained. Also discussed herein are case studies involving pollutants having a wide spectrum of K(ow)s, different types of dissolved organic matters, different pH values and ionic strengths. In most of the case studies, the sorption equilibrium coefficients initially increase with the-concentrations of dissolved organic matters and, then, decrease after reaching a maximum value. This study also addresses the relative errors of partition coefficients attributed to the negligence of the effect caused by the dissolved organic matter, the so-called third-phase effect.     

Degradation of carbofuran in water by solar photocatalysis in presence of photosensitizers

The effect of the presence of photosensitizers, methylene blue (MB) and rose Bengal (RB), on the degradation of carbofuran (2,3-dihydro-2,2-dimethylbenzofuran-7-yl methylcarbamate) in water in a solar photocatalytic system was investigated. It was found that as compared to MB, RB generally showed a stronger effect on the decomposition of carbofuran under comparable conditions. Among the conditions studied, adding 2 x 10(-6) M of RB, that corresponding to 2% of the initial concentration of carbofuran solution in the system, rendered the most effective degradation of carbofuran. As a result, a carbofuran removal percentage of 69.9%, a mineralization efficiency of 28.0%, and a microtoxicity reduction of 65.0% could be achieved. The degradation and mineralization of carbofuran was found to follow the pseudo-first order reaction kinetics. The decomposition mechanism of carbofuran was further investigated through identification of the intermediates to elaborate the influence of dye photosensitizer on the solar photocatalysis of carbofuran in water. On the basis of the intermediates identified, including carbofuran phenol, 3-hydroxy carbofuran phenol, and substituted alcohols (3-phenoxy 1-propanol, 2-ethyl 1-hexanol, 2-butoxyl ethanol), it appears that hydrolysis and hydroxylation were the two key mechanisms for decomposing carbofuran during the process of solar photocatalysis with the aid of dye photosensitizer.     

从低能耗脱盐到资源回收的电容去离子技术在环境领域的研究进展

电容去离子（CDI）技术因具有高效、节能、环保、经济等优异性能,自20世纪60年代发明至今,一直得到研究者的广泛关注。在查阅资料的基础上,从理论研究、工程应用、材料研究3个方面介绍了CDI技术的发展历程,并分析了其理论原理、电化学反应过程、能耗与经济性,并从运行条件和电极优化2个方面对效率的优化提升进行了深入探讨,介绍了CDI技术装置国内外产业化应用情况,提出了CDI技术不仅在脱盐及污水处理领域具有较大发展空间,在环境废物资源化回收方面同样具有广阔的应用前景。     

基于群决策和层次分析法的长江中游地区农村污水处理技术评价及优选

长江流域农村污水治理是实现长江大保护的重要环节,但现有处理技术存在工艺多样、难以选择和缺少评价等问题.因此,调研收集了长江中游地区农村污水处理工程案例资料,分析了不同收集方式和排放标准下各处理技术的应用情况,构建了农村污水处理技术评价指标体系,并基于群决策和层次分析法对各处理技术进行了分类评价.结果表明,长江中游地区农村污水的收集方式以单村或小规模联村收集为主,处理规模主要集中在200 m³·d^-1以下,处理技术以厌氧+生态工艺应用最多(28.05%),一体化设备的应用也较为广泛(22.47%).评价指标体系准则层中技术性能权重最大(0.503 9),其次分别为经济效益(0.247 4)、运行管理(0.155 9)和环境影响(0.092 8),指标层中TP去除率、吨水运行成本、氨氮去除率和维护管理难易的权重较高.评价和优选结果表明,强化生态及厌氧+生态处理技术适于在长江中游农村地区推广和应用.研究结果可为长江中游地区农村污水处理技术的评估选择提供科学依据和参考.     

长江源区草地植被退化对土壤持水能力影响

选择长江源区的格尔木市唐古拉山镇作为研究区,通过野外实地采样与室内测试分析相结合,在分析草地植被不同退化阶段和不同土层深度下土壤持水能力特征的基础上,探讨了草地植被退化对土壤持水能力影响。结果表明：（1）在相同草地植被退化阶段,毛管持水量、饱和含水量和田间持水量随土层深度变化的特征基本一致;在相同土层深度上,毛管持水量、饱和含水量和田间持水量随草地植被退化的特征也大体相同。（2）在相同草地植被退化阶段,土壤持水量总体上随土层深度增加而减少,特别是在未退化阶段,10~20 cm土层的毛管持水量、饱和含水量和田间持水量比0~10 cm土层分别减少了12.38%、33.73%和7.64%。（3）在相同土层深度上,土壤持水量总体上随草地植被退化而减少,特别是在0~10 cm土层,轻度退化阶段的毛管持水量、饱和含水量和田间持水量比未退化阶段分别减少了41.52%、59.95%和27.03%。（4）土壤持水量与土壤容重、总碳、有机质和总氮显著相关,它在草地植被不同退化阶段和不同土层深度下的变化可能与地表覆被状况、植物根系数量和分布特征所引起的土壤容重、有机质等变化有关。研究可深化对草地植被退化与土壤持水能力相互关系的理解和认识,并为长江源区生态环境和水资源状况研究提供参考依据。 关键词： 土壤持水能力;草地植被退化;长江源区;影响     

Photocatalytic oxidation of xenobiotics in water with immobilized TIO2 on agitator

Abstract

A novel photocatalytic oxidation reactor, using Degussa P‐25 T_iO₂ as a stationary phase with a thickness of 1.5–2.0 um on the blades of agitator, was developed to study the photocatalytic oxidation of xenobiotics. Particularly in this device, separation of photocatalyst from the purified water after oxidation reaction was not necessary, and no other aeration equipment was required to supply oxygen. To examine the efficiency of this device, photocatalytic degradation of xenobiotic organics such as carbofuran was studied as an example. Results indicated that carbofuran could be degraded completely with mineralization efficiency of 20 % after 6 hours of oxidation under the imposed conditions. The mineralization rate of carbofuran was found to follow the pseudo‐first order reaction kinetics. Moreover, the rate constant of mineralization was found to be proportional to T_iO₂ film area and the square root of UV light intensity. These results implied the mineralization efficiency of carbofuran could be improved through increasing T_iO₂ film area and UV light intensity. Accordingly, this novel device showed potential application for degrading xenobiotics in water.     

Factors affecting the concentrations of PM10 in central Taiwan

In this study, the synoptic weather types that have high probability and low probability of producing PM10 episode are referred to as HPE and LPE, respectively. Multiple linear regressions analysis showed that NO2 was the most important contributor (35.61%) to the concentrations of PM10 for HPE weather. For LPE weather, the season factor had the greatest contribution (48.11%) to the concentrations of PM10. Using the correlation coefficients between the concentrations of PM10 and SO2 or NO2 on HPE and LPE to calculate the increase of PM10 from LPE to HPE, we found that the increase of PM10 owing to the increase of SO2 and NO2 from LPE to HPE was 12.93microg/m3 which was about 51% of the total amount of PM10 increased from LPE to HPE. Results of factor analysis showed that the first component could be attributed to the result of local pollution especially for the weather patterns of types P3 and P6, while the secondary component for the weather patterns of types P1 and P4 can be attributed to the long-range transport of SO2 pollutants from China.     

Mechanical Properties and Isothermal Crystallization Behaviour of Poly(lactide)/Poly(methyl methacrylate)/α-Cellulose Composites

Polylactide (PLA)/polymethylmethacrylate (PMMA)/α-cellulose composites were fabricated using a twin-screw extruder. During fabrication, α-cellulose short fibres were incorporated for improving the toughness of the brittle PLA and a chain extender was used for reducing PLA hydrolysis. Highly transparent PLA and PMMA were blended to obtain miscible and transparent blends. For evaluating the performance of the PLA/PMMA/α-cellulose composites, a series of measurements, including tensile and Izod impact tests, light transmission and haze measurements, thermomechanical analysis, and determination of isothermal crystallisation behaviour, was conducted. Adding the chain extender considerably reduced the occurrence of hydrolytic degradation. Both the chain extender and α-cellulose short fibres increased the elongation at break and Izod impact strength of the composites. Compared with the neat PLA, including 1.0 wt% α-cellulose short fibres increased the elongation at break and Izod impact strength of the composite PLA by approximately 211 and 219 %, respectively. According to the observed mechanical performance, the optimal blending ratios for PLA and PMMA were between 90:10 and 80:20. The total light transmittance of the composites was as high as 91 %, indicating that the PLA/PMMA blend was highly miscible. The haze value of the PLA/PMMA/α-cellulose composites was lower than 32 %. Incorporating cellulose short fibres increased the number of crystallisation sites and crystallinity of the PLA/PMMA/α-cellulose composites while reducing the spherulite dimensions.     

基于复合LSTM模型的PM2.5浓度预测

在对淄博市19个空气质量监测站点监测数据进行分析后,提出了一种基于机器学习的复合模型——灰色关联度分析(GRA)-改进的完备总体经验模态分解(ICEEMD)-长短期记忆网络(LSTM)模型。通过分析淄博市2019年大气污染物和气象数据,选用LSTM模型预测PM_2.5浓度。由于传统单一模块机器学习模型具有训练时间较长和预测精度较低的问题,提出了复合LSTM模型。该模型由3部分组成：GRA,用于PM_2.5浓度影响因素变量筛选;ICEEMD,用于PM_2.5分解、分量筛选和原始大气污染物及气象数据处理;LSTM,用于PM_2.5浓度预测。预测结果表明：淄博市中部丘陵地带PM_2.5浓度高于南部山区和北部平原,东部高于西部;淄博市逐月PM_2.5浓度呈“U”形分布,1月最高,8月最低;淄博市PM_2.5浓度受PM₁₀和CO影响较大,受湿度和温度影响较小。对比单一LSTM模型和GRA-LSTM模型,GRA-ICEEMD-LSTM模型...