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     

对熏烟扩散模式应用的探讨

工程上应用的大气污染物扩散模式中 ,熏烟模式由于其非定常性而与其他扩散模式有很大的区别。正确处理模式中各参数及变量的相互关系才能客观地反映污染物对环境影响的结果。本研究通过对熏烟模式的非定常性和各参数、变量相互关系的分析 ,提出了正确使用该模式的方法     

Waste minimization and its ecological evaluation A case study in printed circuit board manufacture

The printed circuit board (PCB) manufacturers face several problems regarding the waste they generate. In Austria, a detailed study for waste minimization was carried out with three PCB manufacturers and one electroplating company. In this project a lot of ecologically and economically effective options were found and implemented. The ecological evaluation of processes is still an unsolved problem. Several evaluation models are tested on selected processes of the project.     

以绿化三维量分析植物群降解SO2的宏观效应

控制和降低城市上空ＳＯ２的环境浓度对于改善城市环境，促进城市生态的良性循环具有十分重要的意义。本文从上海市绿化三维量分布模型、与ＳＯ２浓度分布模型的相关分析入手，以季节变化作为对比因子，讨论了城市绿化植物群的数量及分布对城市上空ＳＯ２浓度分布的宏观影响；并据此提出了可有效地控制城市上空ＳＯ２浓度的绿地建设的基本原则。     

Pulse cleaning flow models and numerical computation of candle ceramic filters

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区域环评中大气环境容量估算的研究进展

目前,在大气环境影响评价中,区域大气环境容量的研究是实施大气污染物总量控制的前提.文章综述了大气污染物区域环境容量的主要影响因素、用于其计算的空气质量模型以及大气环境容量研究的一般步骤.现阶段应用较广泛的大气环境容量的预测模型有A-P值法模型、箱模型、线性优化模型、ADMS模型及多种模型相结合的复合模式等,通过研究分析,提出了现阶段大气环境容量研究存在的主要问题及其有效的解决途径.     

Recent developments of surface complexation models applied to environmental aquatic chemistry

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