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     

增压站低频噪声识别与控制

目的解决天然气增压站低频噪声严重的问题,识别低频噪声源,并对低频噪声加以控制。方法结合压缩机组的实际工作情况及结构,首先利用频谱及1/3倍频程分析增压站机组的振动和噪声特性,初步确定压缩站机组低频噪声与机组振动的关系,进一步利用相干函数分析法分析振动与低频噪声的相干关系,判定低频噪声并不是由振动主要引起的。结果机组的主要噪声源为冷却器和压缩缸的进排气管,低频噪声污染主要是由于机组周期性吸排气时,管道和机组壁投射出的空气动力性噪声所造成的,而机组振源的剧烈振动不是产生低频噪声污染的主要原因。进排气管可产生高达80 d B(A)的全频带噪声,其中包含声压级可高达100 dB的次声,尤其以频率11 Hz和17 Hz为主,并且传播距离远,通透力强,对人员和环境危害大。结论首先依据进排气管为主要噪声源,其次结合压缩站实际情况,从压缩器机组整体的降噪设计及厂房治理的降噪设计两部分考虑提出相应的改进措施,从而为机组的降噪提供有效的方法。     

一种模拟动力学边界条件的环境振动试验方法研究

目的提高环境振动试验的可靠性。方法以某典型钛合金蜂窝夹芯壁板试验件为例,提出一种模拟试验件动力学边界条件的试验方法,在试验件周围引入弹性连接件,再通过刚性转接工装与振动台台面连接,以试验件在试验安装状态下的共振频率及振型节线位置为优化目标,以弹性连接件的外形尺寸及厚度为优化变量,对弹性连接件进行优化设计,从而模拟试验件真实的动力学边界条件。结果弹性连接件的优化设计使得试验件在试验安装状态下前两阶共振频率与试验要求相差小于8%,而且振型节线位置与试验要求基本重合,达到了模拟试验件真实动力学边界条件的设计目标。结论对于壁板类试验件,在传统刚性夹具的基础上引入弹性连接件的试验方法,可以较好地模拟试验件真实动力学边界条件,提高环境振动试验的可靠性,并且这种方法对试验费用及试验周期影响较小,具有良好的工程应用前景。     

福州乌鸦咀泉水电导率幅频谱分析初探

地震观测数据受各种周期性因素影响，其动态曲线表现为周期性变化特征，是大小不同的周期和非周期因素相互作用的结果。利用MATLAB工具包，编程幅频分析和滤波程序，以福州乌鸦咀泉水电导率的模拟观测数据为例，对其幅频谱特征和震例进行初步探讨。     

一种超声速气体冲击射流噪声的屏蔽抑制方法

根据对冲击射流离散频率噪声产生的反馈机理的认识，提出了一种能够有效地破坏反馈环的形成，从而抑制冲击射流离散频率噪声的喷嘴屏蔽方法。这种方法是通过阻隔反馈声波使其不能到达喷嘴唇口、同时屏蔽物不与射流接触来实现降噪的目的，实验结果表明，对于合适的屏蔽罩参数，正常降噪效果达5dB以上。分析表明这种降噪方法对射流冲击平板的推力和除尘除水效率的提高有帮助。     

煤矿风井轴流风机噪声控制设计计算

煤矿风井轴流风机气流速度大,扩散口噪声辐射强度高达113dB(A),降噪难度较大的低频成份突出。正确合理的低频噪声控制设计计算是噪声控制成功的关键。     

小鼠微核试验检测大气颗粒物致突变性

以小鼠微核试验检测上海市有代表性的13个点大气颗粒物的致突变活性,结果表明,上海市大气颗粒物有机提取物能引起小鼠骨髓嗜多染红细胞微核率的升高,且有剂量-反应关系,而各采样点的致微核作用相似.     

极低频电磁场对健康影响的流行病学调查及人体测试研究进展

流行病学调查结果表明，环境的极低频电磁场暴露与人群某些肿瘤，如白血病、乳腺癌、脑肿瘤等，以及生殖、神经、心血管和内分泌等系统疾患的发病相关，这些结果在一定程度上得到实验室人体测试的支持。然而，极低频电磁场对健康影响的确切效应，迄今尚未能作出结论，亟等进一步开展多层次、多水平的研究。     

高频电磁辐射防护材料的研究

电磁污染已经成为一种不容忽视的全球性社会公害。因此，本文通过测量多种材料在不同高频电磁场源（即高频设备）和不同距离时对高频电磁场的屏蔽效率，获得了大量数据，并对所测数据用最小二乘法进行拟合处理，绘出了这些材料在不同高频场源下的屏蔽效果曲线。经分析，筛选出经济实用的高频近区场个人防护材料，具有推广应用的价值。