SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

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     

Epidemiologic Analysis of Factors Associated with Local Disappearances of Native Ranid Frogs in Arizona

Abstract:  We examined factors that may independently or synergistically contribute to amphibian population declines. We used epidemiologic case–control methodology to sample and analyze a large database developed and maintained by the Arizona Game and Fish Department that describes historical and currently known ranid frog localities in Arizona, U.S.A. Sites with historical documentation of target ranid species ( n = 324) were evaluated to identify locations where frogs had disappeared during the study period (case sites) and locations where frog populations persisted (control sites). Between 1986 and 2003, 117 (36%) of the 324 sites became case sites, of which 105 were used in the analyses. An equal number of control sites were sampled to control for the effects of time. Risk factors, or predictor variables, were defined from environmental data summarized during site surveys and geographic information system data layers. We evaluated risk factors with univariate and multifactorial logistic-regression analyses to derive odds ratios (OR). Odds for local population disappearance were significantly related to 4 factors in the multifactorial model. Disappearance of frog populations increased with increasing elevation (OR = 2.7 for every 500 m, p < 0.01). Sites where disappearances occurred were 4.3 times more likely to have other nearby sites that also experienced disappearances (OR = 4.3, p < 0.01), whereas the odds of disappearance were 6.7 times less (OR = 0.15, p < 0.01) when there was a source population nearby. Sites with disappearances were 2.6 times more likely to have introduced crayfish than were control sites (OR = 2.6, p = 0.04). The identification of factors associated with frog disappearances increases understanding of declines occurring in natural populations and aids in conservation efforts to reestablish and protect native ranids by identifying and prioritizing implicated threats.     

Prenatal diagnosis of Apert syndrome: report of two cases

Two de novo cases with Apert Syndrome detected prenatally are presented herein. In the first, fetal ultrasound findings of syndactyly of the hands, craniosynostosis and proptosis resulted in a prenatal diagnosis in the nineteenth week of gestation. This is the earliest prenatal diagnosis of this syndrome in a not-at-risk case. Following counseling, this pregnancy was terminated and subsequent pathological examination and DNA analysis confirmed the diagnosis of Apert Syndrome and coarctation of the aorta. In the second case, fetal ultrasound at 21 weeks' gestation revealed a hypoplastic left heart and clover-leaf skull. Following counseling, this pregnancy was also terminated. Further examination of the fetus and DNA analysis led to a diagnosis of Apert Syndrome. These cases emphasize the need to complete a thorough fetal ultrasound in cases with potentially lethal cardiac abnormality and the importance of incorporating a fetal pathologist, as well as a medical geneticist, in the investigations performed after delivery or pregnancy termination when a fetal abnormality is detected on ultrasound. Copyright © 2003 John Wiley & Sons, Ltd.     

生态足迹影响因子的定量分析

人口的膨胀和人类工业化进程的加剧，使得人类向自然界获取越来越多的资源，同时向环境源源不断的输入废弃物，已经严重超过了自然生态系统的供给能力和环境容量，生态环境日益恶化，水土流失、草场退化、植被消亡、生物多样性锐减、全球变暖等情况已经严重到难以遏制的地步，危及到人类自身的生存。在和平与发展成为世界两大主题的今天，人们越来越关注可持续发展的问题。在现有资料的基础上，利用主成分分析方法，定量地讨论了中国各省（区市）1999年生态足迹大小与其影响因子间的关系。结果表明，生态足迹的大小是各省（区市）的大中型企业个数、全社会固定生产投资等众多因子共同作用的结果，其中总人口和GDP是生态足迹大小的主要影响因子，其因子载荷量分别达到了0.940和0.913。值得一提的是非农业人口与生态足迹的相关系数超过了农业人口，这说明由于消费模式和生活水平等的差异，非农业人口对生态足迹的影响大于农业人口对生态足迹的影响。在此基础上建立了生态足迹影响因子的多元线性回归模型，以期为生态足迹在进行区域可持续发展评价的方法上提供新的思路。     

中国可持续社会养老保险的综合评价体系和实证分析

我国可持续社会养老保险的综合评价指标体系包括四个层次和三级子系统，内容涉及养老保险人数、机构设置、基金管理和代际平衡四个子目标。应用因子分析模糊综合评价方法对我国1990-2001年养老保险建设状况进行评价，本文认为基金管理，行政管理和代际失衡是影响我国可持续养老保险发展的主要因素。     

Pitfalls in molecular diagnosis in a family with severe factor VII (FVII) deficiency—misdiagnosis by direct sequence analysis using a PCR product

Molecular diagnostic tests are becoming a routine analysis in many laboratories. These modern analyses are widely used in clinical medicine, forensic, genetic and prenatal diagnosis and also in preimplantation genetic diagnosis. The accuracy of analysis is highly dependent on the success achieved in minimising genotyping errors. The pitfalls in molecular diagnostic tests can be due to a simple technique such as the polymerase chain reaction (PCR) used universally. This technique is routinely used for its apparent accuracy, but it is also a well-known source of errors. We report an error introduced during PCR reaction that leads to a wrong sequence result and consequently to a ‘false’ molecular result in a next prenatal diagnosis in a family with severe factor VII (FVII) deficiency. This error was verified using an unsuitable primer design in a rich repetitive sequence of the FVII gene that leads to a false annealing and then to a wrong molecular diagnosis. It is essential to link closely molecular data with clinical and phenotype analysis in order to avoid false-negative or false-positive results, which is of great importance to diagnosis and molecular prevention. Copyright © 2003 John Wiley & Sons, Ltd.     

亚热带稻田土壤碳氮磷生态化学计量学特征

为了解稻田土壤中是否存在稳定的土壤有机碳(C)、氮(N)和磷(P)比值,基于亚热带区110个水稻土剖面和587个发生层的土壤调查数据库,在区域尺度上分析了典型水稻土C∶N∶P比值的生态化学计量学特征,并应用相关分析和冗余分析,研究水稻土C∶N∶P比值与土壤-环境因子(地形和母质、土壤发生层、土壤类型和土壤理化性质)的关系.结果显示,亚热带区稻田土壤C∶N、C∶P和N∶P的剖面加权平均值分别为12. 6、49和3. 9,C∶N∶P为38∶3. 2∶1.不同母质起源、不同土壤亚类和不同发生层的水稻土C∶N变异相对较小;但C∶P和N∶P的变异很大,两者均值也远低于全球(186和13. 1)和中国土壤(136和9. 3)的C∶P和N∶P的平均水平.尽管稻田土壤剖面的C∶N∶P相对不稳定,但由于稻田表土生物与环境相互作用强烈,表土C∶N相对稳定(14. 2).这反映长期水耕熟化作用下,稻田表土中C和N仍存在紧密的耦合作用.然而,在稻田土壤剖面上,C∶P和N∶P并不稳定,SOC与全P含量、全N与全P含量也无显著相关性,表明环境变化可能导致土壤C∶N∶P解耦.地形、土壤质地、氧化铁和容重是调控稻田土壤剖面C∶N∶P的关键土壤环境因子.     

北京市农业机械排放因子与排放清单

利用车载排放测试技术对典型的联合收割机、拖拉机、农用运输车和农田建设机械实际工况下的尾气进行测试,建立了实际工况下农业机械的排放因子和2017年北京市农用机械排放清单.结果表明,不同的工作状态对农业机械尾气排放有较大的影响,怠速和行走时CO、NO_x、HC和PM排放趋于平稳;而切地和翻地模式下的波动较为明显.根据各类机械的分类和排放标准对排放因子进行细化,建立了较为完整的实际工况下的排放因子.根据农业机械排放因子和燃油消耗量计算出2017年北京市CO、NO_x、HC和PM的排放量分别是2 566.60、 1 239.29、 563.08和538.32 t.拖拉机、运输机械和联合收割机的污染物总量占CO、NO_x、HC和PM这4种污染物总量的98%、 95%、 95%和98%.因此,农用拖拉机、运输机械和联合收割机在农业机械污染减排中应作为重点控制对象.