青岛市区春夏季大气能见度与颗粒物的关系

利用青岛市灰霾综合观测站2012年3月2日-2012年6月7日期间的监测数据,分析了青岛市区大气能见度与不同粒径颗粒物质量浓度的日变化特征,比较了各级别大气能见度下不同粒径颗粒物质量浓度及所占比例的相关性,研究了相对湿度对大气能见度和颗粒物质量浓度相关性的影响.结果表明,监测时段大气能见度与颗粒物质量浓度呈现较好的负相关,每天大气能见度最低值出现在早晨07:00--09:00;剔除相对湿度高于90％的前提下,PM2.5是影响大气能见度的主要因子,随着其在PM1o中所占比例上升,大气能见度级别不断下降,相关系数为-0.84;不同相对湿度区间下,PM2.5对大气能见度的影响最明显,其中,相对湿度为60％ ～ 70％,大气能见度与颗粒物质量浓度之间的相关性最好.     

Application of Multiattribute Decision-Making Methods for the Determination of Relative Significance Factor of Impact Categories

A relative significance factor (f _i ) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f _i . Multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f _i . Thus, all three methods can be applied to the determination of f _i . The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f _i because it is easier and simpler to use compared to the AHP and the fuzzy method.     

影响上海地区热带气旋频数的预测水平评估

在文献「１」研究的基础上，探讨了热带气旋频数预测水平的评估方法，定义了三个更适合于评估每年热带气旋预测性能的参数，对影响上海地区热带气旋频数的预测水平进行了评估，并与“九五”攻关前的业务预测性进行了比较。     

Octanol–air partition coefficients of polybrominated biphenyls

The octanol–air partition coefficients (K_OA) for PBB15, PBB26, PBB31, PBB49, PBB103 and PBB153 were determined as a function of temperature using a gas chromatographic retention time technique with 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (p,p′-DDT) as a reference substance. The internal energies of phase change from octanol to air (Δ_OAU) were calculated for the six compounds and were in the range from 74 to 116 kJ mol⁻¹. Simple regression equations of log K_OA versus relative retention times (RRTs) on gas chromatography (GC), and log K_OA versus molecular connectivity indexes (MCI) were obtained, for which the correlation coefficients (r²) were greater than 0.985 at 283.15 K and 298.15 K. Thus the K_OA values of the remaining PBBs can be predicted by using their RRTs and MCI according to these relationships.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Wall losses of oxygenated volatile organic compounds from oxidation of toluene: Effects of chamber volume and relative humidity

Vapor wall losses can affect the yields of secondary organic aerosol. The effects of surface-to-volume (S/V) ratio and relative humidity (RH) on the vapor-wall interactions were investigated in this study. The oxygenated volatile organic compounds (OVOCs) were generated from toluene-H₂O₂ irradiations. The average gas to wall loss rate constant (k_gw) of OVOCs in a 400 L reactor (S/V = 7.5 m⁻¹) is 2.47 (2.41 under humid conditions) times higher than that in a 5000 L reactor (S/V = 3.6 m⁻¹) under dry conditions. In contrast, the average desorption rate constant (k_wg) of OVOCs in 400 L reactor is only 1.37 (1.20 under humid conditions) times higher than that in 5000 L reactor under dry conditions. It shows that increasing the S/V ratio can promote the wall losses of OVOCs. By contrast, the RH effect on k_gw is not prominent. The average k_gw value under humid conditions is almost the same as under dry conditions in the 400 L (5000 L) reactor. However, increasing RH can decrease the desorption rates. The average k_wg value under dry conditions is 1.45 (1.27) times higher than that under humid conditions in the 400 L (5000 L) reactor. The high RH can increase the partitioning equilibrium timescales and enhance the wall losses of OVOCs.     

Comparing the sensitivity of soil invertebrates to pesticides with that of Eisenia fetida

The sole routine testing of the standard earthworm Eisenia fetida for the terrestrial risk assessment of pesticides has been under much debate since other soil invertebrates may be more sensitive than this standard test species. However, the very low availability of laboratory toxicity data for taxa other than E. fetida has greatly hampered sensitivity comparisons. In the present study, the relative tolerance (T_rel) approach was used to enable comparing toxicity thresholds obtained from the US-EPA ECOTOX database, for main terrestrial taxonomic groups and pesticidal types of action (insecticides, fungicides, herbicides, and other) separately. Analyses confirmed previously reported lower and higher sensitivity of collembolans to fungicides and insecticides, respectively. However, various other discrepancies in susceptibility relative to E. fetida were encountered as indicated by species sensitivity distributions and/or calculated 95% confidence intervals of T_rel values. Arachnids and isopods were found to be more sensitive to insecticides, and nematodes to fungicides, as compared to E. fetida. Implications of study findings for the terrestrial risk assessment of pesticides are discussed.     

金竹山土朱煤矿开采地表沉降规律与灰色预测模型研究

针对金竹山矿业公司土朱煤矿煤层赋存条件,依据采动理论的裂缝垂直分带模型,分析地表沉降和塌陷的机理;提出在采煤活动阶段应进行地表实际位移观测,经数据处理后得到地面沉降曲线,以确保地面人类活动的安全;在采煤活动后阶段则实施灰色预测地面沉降,即通过采煤活动阶段的地表实际观测数据为历史原始数据序列,建立灰色Logistic模型;并对采煤活动后阶段的地面沉降进行预测。精度检验表明:灰色Logistic模型预测精度高,利用该模型预测地面沉降可减少地面沉降监测经费和实时提供预警信息,以确保开采区域内人们生命财产安全。     

Using Relative Risk to Compare the Effects of Aquatic Stressors at a Regional Scale

The regional-scale importance of an aquatic stressor depends both on its regional extent (i.e., how widespread it is) and on the severity of its effects in ecosystems where it is found. Sample surveys, such as those developed by the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program (EMAP), are designed to estimate and compare the extents, throughout a large region, of elevated conditions for various aquatic stressors. In this article, we propose relative risk as a complementary measure of the severity of each stressor’s effect on a response variable that characterizes aquatic ecological condition. Specifically, relative risk measures the strength of association between stressor and response variables that can be classified as either “good” (i.e., reference) or “poor” (i.e., different from reference). We present formulae for estimating relative risk and its confidence interval, adapted for the unequal sample inclusion probabilities employed in EMAP surveys. For a recent EMAP survey of streams in five Mid-Atlantic states, we estimated the relative extents of eight stressors as well as their relative risks to aquatic macroinvertebrate assemblages, with assemblage condition measured by an index of biotic integrity (IBI). For example, a measure of excess sedimentation had a relative risk of 1.60 for macroinvertebrate IBI, with the meaning that poor IBI conditions were 1.6 times more likely to be found in streams having poor conditions of sedimentation than in streams having good sedimentation conditions. We show how stressor extent and relative risk estimates, viewed together, offer a compact and comprehensive assessment of the relative importances of multiple stressors.