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     

滤纸法测定悬浮物的干扰及其消除

提出了滤纸法测定悬浮物时，水样的酸碱度，取样量的多少对悬浮物测定有直接的影响。通过实验验证，对于偏酸，偏碱的水样用酸碱中和后再过滤即可消除影响，取样量应根据悬浮物的不同而定。     

湖州市北污水处理厂污泥处理运行管理

重点介绍湖州市北污水处理厂采用带式压滤机进行污泥脱水处理的应用情况及运行管理,并进行了小结。     

恶臭污染防治技术及工程实践

目前，恶臭污染对人类生活的危害日益加剧，文中介绍了几种恶臭污染物的防治技术。对生物滴滤池 活性炭吸附工艺进行了探讨，工程实例表明具有良好的治理效果。     

上海市雨水污染控制初探

水环境的严重污染和饮用水资源的匮乏，已对上海市的持续发展构成了直接和潜在威胁。在借鉴国外雨水处理利用的研究，应用成果，综合考虑上海市水环境，城市建设及经济发展现状和地区特点的基础上，对上海地区城市雨水污染及其特性，控制雨水污染措施等作了阐述。     

浅淡大阻力配水系统的技术改造

大阻力配水系统滤池由于采用穿孔钢管配水 ,而穿孔钢管容易腐蚀、结垢 ,导致孔眼堵塞 ,再若高位水箱反冲强度掌握不当 ,会使承托层和滤料冲洗混乱 ,滤池不能正常运行。针对这一问题 ,湖州市自来水公司与浙江省玉环净化厂联手 ,利用该厂滤板、滤头及有关专利新技术 ,对自来水公司的 6万t/d快速滤池进行改造 ,运行半年来 ,取得了满意的结果。     

锦纶生产废水的深度处理研究

采用曝气生物滤池对锦纶生产废水进行深度处理,试验结果表明,该工艺可有效去除CODCr和NH3-N,并在不同运行条件下的运行特性进行了考察,确定试验的最佳气水比。     

电凝聚过程中消除电极钝化方法的研究进展

电凝聚法是一种对环境二次污染很小的废水处理技术，具有广阔的应用前景。但是,因其电化学过程中可溶性铝或铁阳极的钝化现象而限制了其高效低能耗应用。从电凝聚电极过程的分析入手，讨论了电极钝化的本质原因及消除电极钝化的措施,并介绍了笔者采用自行研制的交变脉冲电凝聚专用电源,彻底消除电极钝化方面的研究进展。     

空气过滤技术研究综述

文章分别从空气过滤材料、空气过滤器、空气过滤理论及空气过滤技术的应用等四个方面,对空气过滤技术进行了详细阐述.总结了空气过滤材料、空气过滤器的分类及研究进展、空气过滤器的过滤机理及过滤理论的发展.介绍了空气过滤技术的主要应用,并指出了空气过滤技术的发展动向和市场趋势.     

STC脉冲喷吹袋式除尘器在机立窑烟气除尘脱硫中的应用

介绍了STC脉冲喷吹袋式除尘器的自动控温、外滤除尘、自控离线脉冲喷吹清灰的工作原理和特点 ,监测数据说明该除尘器成功解决了机立窑消烟、除尘和脱硫问题