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     

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用煤矸石制取水玻璃的研究

本文研究了用煤矸石制取水玻璃的可行性，利用正交试验，研究了焙烧温度、焙烧时间、反应温度、ＮａＯＨ浓度、渣样粒度等因素对制取过程的影响，确定了最佳操作条件。     

红外和热分析联用在化工产品研究中的应用

运用实例论述了红外光谱分析与热分析联用在化工产品的产品开发和检测方面的应用。     

FRP加固钢筋混凝土梁的抗剪计算方法

随着利用FRP加固混凝土结构研究的深入和应用的拓展,FRP加固钢筋混凝土梁抗剪性能的研究已取得了丰硕的成果。以往对抗剪承载力的分析大多是基于有效应变即对极限应变进行有效折减的方法,而最近的研究则引入了裂缝处FRP应变分布不均匀系数。在此基础上,本文综合考虑了FRP发挥的最大应变、沿裂缝应变分布的不均性以及斜裂缝倾角对有效应变的影响,提出了等效有效应变的概念,使计算趋于简单和清晰。本文收集了128根FRP全包裹的、以FRP断裂破坏为主的钢筋混凝土梁的抗剪实验数据,通过对主要影响因素的统计分析,建立了等效有效应变简单可靠的计算公式和基于FRP断裂的抗剪承载力设计方法。128根实验梁的抗剪计算结果表明,本文提出的方法简单可行,意义明确,且精度要比已有的建议公式稍高。     

基于热带海洋大气环境下机载PCB板的环境适应性对比研究

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工程塑料环境因素与载荷应力耦合作用试验装置研究

目的 设计一种能够模拟工程塑料实际服役工作环境的试验装置,在多型自然环境中,构建兼具环境因素侵蚀与载荷应力耦合作用的试验条件。方法 研制工程塑料环境因素与载荷应力协同作用试验装置,采用包括拉伸加载、弯曲加载、控制系统等组件的模块化设计,实现0.01~16 Hz加载频率的拉伸及弯曲载荷,最大1 550 kg的拉伸载荷,最大375 kg的弯曲载荷。结果 将研制完成的试验装置置于多型自然环境下对试验施加恒定和交变载荷,以真实模拟工程塑料实际服役中的环境因素与载荷应力协同作用。结论 试验装置制造加工难度小,结构稳定可靠,可用于评价和研究工程塑料等系列类型材料的环境损伤性能演变。     

基于Arrhenius模型和Peck模型的分段非线性加速模型

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