Coat color polymorphism in populations of the northern mole vole in the Ural Region

Collections made in the course of long-term field studies on ecology of the northern mole vole Ellobius talpinus Pall. in the Ural Region and neighboring areas (more than 2000 individuals from 24 points of the species range) were used to analyze geographic variation in its coat color (color morphs). On the basis of long-term observations (1985–1999) on marked animals from a polymorphic population (Kurtamyshskii raion, Kurgan oblast), the life spans of males and females and the dependence of life span on population density and structure were estimated in animals of different color morphs. Each color morph of E. talpinus was shown to have specific features of the seasonal dynamics of age structure and migrations.     

Municipal anaerobic digesters for codigestion, energy recovery, and greenhouse gas reductions.

Codigestion of five wastes and municipal wastewater sludge was evaluated using full-scale testing. Synergistic, antagonistic, and neutral outcomes were observed depending on codigestate identity and concentration, highlighting the value of careful blending. Yeast waste resulted in notable synergism, increasing biogas production by over 50%, whereas aircraft deicing waste resulted in antagonism at high loadings and neutral outcomes at lower loadings. Restaurant waste codigestion resulted in neutral outcomes. The synergisim with yeast codigestates may have resulted from trace nutrients (i.e., iron, nickel, and cobalt) in the wastes that increased microbiological activity. Antagonist outcomes with deicing waste may have been the result of organic overload or inhibitory deicer constituents. Codigestion of wastes at the feed rates investigated was estimated to produce 0.50 ML/d of methane having an energy equivalent of 17 500 MJ/d. This was estimated to reduce net carbon dioxide emissions by 560 tonnes/y.     

Analysis of polycyclic aromatic hydrocarbons (PAHs) in airborne particles by direct sample introduction thermal desorption GC/MS

The technique of thermal desorption (TD)–GC/MS was evaluated for measuring airborne, 4–6 ring polycyclic aromatic hydrocarbons (PAHs) collected onto quartz filters. TD provides a more readily automated and sensitive alternative to traditional solvent extraction, decreasing the time/cost of analysis and reducing the risk of analyte loss or sample contamination. The developed method was successfully applied to the analysis of PAH standard solutions loaded on sorbent tubes packed with quartz wool and the graphitized carbon black sorbent Carbograph2. The optimized method showed high desorption efficiency over the whole range of target PAHs with good precision, linearity and sensitivity. The proposed method was verified on an urban dust Standard Reference Material (SRM 1649a); the experimentally determined concentrations agreed with the certified ranges (95% confidence limit) for all target compounds except benzo[a]anthracene, which fell just outside the narrow certified range. The desorption efficiency and the reproducibility of the method was evaluated by analysing pieces of real sample filters sampled from urban air for a period of 24 h. The results confirmed the homogeneity of the filter and showed high recovery efficiencies for all target PAHs.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

灰色协调度模型在产业用水系统分析中的应用

揭示产业用水系统的时空动态发展规律，探讨其内部的协调关系，是开展节水型社会建设规划，实现水资源可持续利用的关键。然而，目前对产业用水系统的协调性分析还缺乏较为有效的理论和方法。以往在利用协调度模型进行用水系统有序度研究时，通常采用两段叙述的线性分段函数表示，较不适用于描述产业用水系统内部要素的非线性结构。因此，针对产业用水系统的特性，利用灰关联原理建立有序度函数，以建立更适于用水系统分析的灰色协调度模型。利用该模型对上海市1997~2005年产业用水系统进行实证研究，结果显示：上海市产业用水系统基本有序，发展比较协调，其用水综合效益较大，但距离最优状态尚有潜力可挖；其中，农业用水子系统的发展较为欠缺，在未来用水规划中应予以重视。