Dust Storms are an Indication of an Unhealthy Environment in East Asia

Dust storms frequently occur in Mongolia and in northern China. Each year there are 30 to 120 dusty days in source regions of Mongolia and 14–20 dusty days on the Korean Peninsula. Intense sand storms and associated dust falls produce environmental impacts in East Asia. This paper discusses the environmental degradation in Mongolia and the social, economic and atmospheric impacts of dust storms in the sink area. The impact of dust storms on environmental compartments as well as their direct and indirect consequences to basic resources like water and energy demand and supply is explained. Governments are encouraged to take appropriate action in specified regions. For monitoring dust storms there is a need for international cooperation to combat growing environmental and human security concerns.     

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1-June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1-December 31), and the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash-Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.     

污水灌溉风险概率分布的研究

针对目前我国水资源紧缺、用大量污水进行农田灌溉造成环境污染的现状,指出了污水灌溉风险研究中的不足.利用农业干旱模型,通过非参数检验对污水灌溉风险的概率分布进行了研究,并利用江苏省南京地区某污灌区的实际资料,计算了当地污水灌溉风险的概率分布.     

区域水战略方案选优的动态组合评价模型研究

水安全危机是人类进入新世纪以来在生存及发展方面所面临的最严重挑战之一。研究科学合理的水安全战略成为区域可持续发展的重大课题。针对区域水战略问题涉及众多因素且各因素之间动态关联的特点，提出了基于水战略方案优选的兼容度极大化动态组合评价模型（CMM—DCEM），并将其成功地应用于我国广东省北江下游及其三角洲地区水安全战略方案优选评价。评价结果及模型基于不确定性的敏感性分析结果证明：CMM—DCEM实现了主、客观赋权方法以及单一评价模型的融合，使用实码加速遗传算法求解目标函数，克服了传统的组合评价方法计算繁琐的不足，评价过程更加科学合理。     

Gas chromatographic methods for monitoring of wastewater chlorophenol degradation in anaerobic reactors

Wastewater samples from an anaerobic reactor were extracted with hexane and derivatized with diazomethane (method 1) and with acetic anidride (method 2). Gas chromatography with electron-capture detection (ECD) was employed for separating the parent compound and intermediates trichlorophenols (TCP) and dichlorophenols (DCP) which originated from the penta chlorophenol (PCP) degradation process. The relations between concentrations of PCP, TCP and DCP areas were linear in the range of concentrations of 0.2 to 8 mg/L and 0.025 mg/L to 5 mg/L for methods 1 and 2, respectively. The repeatability of the extraction methods was satisfactory, with variation coefficients lower than 11%. For method 1, at the fortification level of 0.2 mg/L, recovery of PCP, TCP, and DCP was 112%, 74% and 45%, respectively. For method 2, the corresponding recovery values at the fortification level of 0.1 mg/L were 91%, 93% and 103%, respectively. Storage of the frozen samples did not alter their PCP determination properties. The chromatographic methods adapted for chlorophenol determination in wastewater were suitable with relatively simple manipulation techniques. The obtained results were reproducible and allowed identification of intermediates formed during the PCP degradation process.     

A directional passive air sampler for monitoring polycyclic aromatic hydrocarbons (PAHs) in air mass

A passive air sampler was developed for collecting polycyclic aromatic hydrocarbons (PAHs) in air mass from various directions. The airflow velocity within the sampler was assessed for its responses to ambient wind speed and direction. The sampler was examined for trapped particles, evaluated quantitatively for influence of airflow velocity and temperature on PAH uptake, examined for PAH uptake kinetics, calibrated against active sampling, and finally tested in the field. The airflow volume passing the sampler was linearly proportional to ambient wind speed and sensitive to wind direction. The uptake rate for an individual PAH was a function of airflow velocity, temperature and the octanol-air partitioning coefficient of the PAH. For all PAHs with more than two rings, the passive sampler operated in a linear uptake phase for three weeks. Different PAH concentrations were obtained in air masses from different directions in the field test.     

好氧颗粒污泥对有机物吸附类型的研究

为探索好氧颗粒污泥对有机物的去除机制,进行好氧颗粒污泥对有机物的吸附性能及吸附类型研究,在实验室条件下,采用动态吸附方式,利用SBAR反应器分析好氧颗粒污泥对有机物的去除情况。结果表明,好氧颗粒污泥存在初期吸附作用,最佳吸附时间为30~45 min,COD去处率60%;通过对失活前后好氧颗粒污泥对有机物吸附性能测定以及红外光谱分析,探究好氧颗粒污泥对有机物的吸附类型,表明好氧颗粒污泥对有机物的吸附是一个包含生物吸附和化学吸附的复杂过程。     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

高灵敏XRF测定废水中痕量砷

本文提出了在硫酸介质中，以锌粒还原产生氢化物，溴化铜溶液吸收，微孔滤膜过滤制成薄样，Ｘ射线荧光测定水中痕量砷的分析方法。