Effects of adsorption onto silica sand particles on the hydrolysis of tetracycline antibiotics

Due to high usage of tetracycline antibiotics, concerns have been raised about their environmental fate. In this study, potential changes in the pseudo-first-order hydrolysis rate constants for three tetracyclines, tetracycline (TC), oxytetracycline (OTC) and chlortetracycline (CTC), were evaluated by measuring the rate constants in batch and column leaching experiments. The first-order hydrolysis rate constants were measured at pH 5, 7, and 9 using batch tests. The values were highest at pH 7 for all three tetracyclines (0.0030 ± 0.0004, 0.0042 ± 0.0001, and 0.0323 ± 0.0003 h(-1) for TC, OTC, and CTC, respectively), indicating relatively short environmental half-lives of tetracyclines. Interestingly, it was found that the rates of degradation of the parent tetracyclines were much faster when silica sand was present in a batch solution or when the solution was passed through a silica column. For example, the ratios of the first-order degradation rate constants obtained in the column experiments to those in batch experiments were 13.2, 2.1, and 2.0 for TC, OTC, and CTC at a volumetric flow rate of 0.08 mL h(-1), with an observed tendency for this ratio to increase with an increased flow rate. This indicates that the silica surface may serve as a catalyst for hydrolysis and that the actual environmental half-lives of tetracycline antibiotics could be shorter than those estimated from laboratory hydrolysis rate constants using the standard batch protocol. Furthermore, the toxicity of the column effluent containing hydrolysis metabolites was assessed using bioluminescence inhibition in Vibrio fischeri. It was estimated that the toxicity of the metabolites of CTC was lower than that of their parent compound, whereas the toxicity of metabolites of TC and OTC was as high as or higher than that of their parent compounds.     

水样发光细菌急性毒性测试的方式与表征

选取不同类型的环境和污染源水样开展了发光细菌毒性测试,针对不同环境管理目标,探讨了急性毒性定量表征方式。发光细菌急性毒性测试在环境应急监测、水源早期生物预警中,采用绘制毒性预警基线图的方式比较可行。在污染源监督监测中,对于发光抑制率低于60%、无法求出EC50的样品,采用等效毒性参照物的质量浓度表征废水的毒性;对于发光抑制率高于60%,采用稀释因子表示样品的毒性更直观可靠。     

Assessment of trace element contamination in sediment cores from the Pearl River and estuary,South China: geochemical and multivariate analysis approaches

Twenty-four major and trace elements and the mineralogical composition of four sediment cores along the Pearl River and estuary were analyzed using ICP-AES, ICP-MS, and X-ray diffraction (XRD) to evaluate contamination levels. The dominant minerals were quartz, kaolinite, and illite, followed by montmorillonite and feldspars, while small amounts of halite and calcite were also observed in a few samples. Cluster analysis (CA) and principal component analysis (PCA) were performed to identify the element sources. The highest metal concentrations were found at Huangpu, primarily due to wastewater treatment plant discharge and/or the surreptitious dumping of sludge, and these data differed from those of other sources. Excluding the data from Huangpu, the PCA showed that most elements could be considered as lithogenic; few elements are the combination of lithogenic and anthropogenic sources. An antagonistic relationship between the anthropogenic source metals (K, Ba, Zn, Pb, Cd, Ag, Tl, and U) and marine source metals (Na, Mg, Ti, V, and Ca) was observed. The resulting normalized Al enrichment factor (EF) indicated very high or significant pollution of Cd, Ag, Cu, Zn, Mo, and Pb at Huangpu, which may cause serious environmental effects. Conflicting results between the PCA and EF can be attributed to the background values used, indicating that background values must be selected carefully.     

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。     

A dynamic compartment model for assessing the transfer of radionuclide deposited onto flooded rice-fields

A dynamic compartment model has been studied to estimate the transfer of radionuclides deposited onto flooded rice-fields after an accidental release. In the model, a surface water compartment and a direct shoot-base absorption from the surface water to the rice-plant, which are major features discriminating the present model from the existing model, has been introduced to account for the flooded condition of rice-fields. The model has been applied to the deposition experiments of 137Cs on rice-fields that were performed at three different times to simulate the deposition before transplanting (May 2) and during the growth of the rice (June 1 and August 12), respectively. In the case of the deposition of May 2, the root-uptake is the most predominant process for transferring 137Cs to the rice-body and grain. When the radionuclide is applied just after transplanting (June 1), the activity of the body is controlled by the shoot-base absorption and the activity of the grain by the root-uptake. The deposition just before ear-emergence (August 12) shows that the shoot-base absorption contributes entirely to the increase of both the activities of the body and grain. The model prediction agrees within one or two factors with the experimental results obtained for a respective deposition experiment.