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     

受侧向土体位移斜桩的特性

通过三维有限单元法分析了斜桩受侧向土体位移的特性。变动柱和土体参数进行敏感性分析,得出桩的柔度、侧向土体位移的大小、桩顶约束条件、土体位移形状和土体移动层厚度等对斜桩的影响。刚性桩的挠度小于柔性桩,但弯矩和剪力大于柔性桩。斜桩非线性弹簧的土抗力—位移关系(p-y曲线)表现为双曲线特征,可基于直桩的Winkler地基反力法对斜桩进行简化计算分析,但应对直桩的极限土抗力值进行修正,以期更好的反映斜桩的特性。     

Stability of a Coal Waste Artificial Reef

The feasibility of using U.K. coal-fired power station waste materials for artificial reef production is being examined. in June, 1989, an experimental artificial reef was constructed in Poole Bay, off the central south coast of the U.K., using three different mixtures of pulverised fuel ash (PFA), flue gas desulphurisation (FGD) gypsum and slurry, stabilized with cement and formed into blocks. Fifty tonnes of 40 × 20 × 20 cm blocks were formed into eight conical reef units replicating three different PFA/gypsum mixtures and one concrete control. the reef structure is 10m below chart datum on a flat sandy sea-bed.

Combustion of coal concentrates the heavy metal content in the resultant ash. the purpose of stabilization of the ash as blocks is twofold: to immobilize heavy metals (or other components) and to provide hard substratum for the attachment of organisms. to examine the effectiveness of this stabilization and hence the environmental compatibility of the block materials, heavy metal (Cd, Cr, Cu, Pb, Mn, Ni, Zn) content of the blocks has been monitored routinely over two years, to determine leaching rates. Sectional profiles indicate partial replacement of calcium content by magnesium. Associated with this there has also been some redistribution of heavy metals. Only in the case of cadmium has there been a detectable loss from the surface of blocks. Chromium and manganese concentrations appear to have increased. the metal content of the reef epibiota (including ascidians, Ascidia mentula; hydroids, Halecium spp.; bryozoans, Bugula spp. and red algae) growing on the ash blocks has been compared to that of epibiota attached to the concrete controls and surrounding sea-bed. to date no evidence of excess bioaccumulation of metals has been detected.

The physical integrity of the ash reef blocks has been maintained. There is evidence that the blocks are increasing in compressive strength.

An indication of the fishery enhancement potential of the experimental structure is given by the presence of eight commercially fished species (crustaceans and molluscs) including lobsters (Homarus gammarus).     

三峡库区中低产土壤重金属含量及其与小麦吸收的关系

三峡库区中低产土壤的Hg,As,Cr,Pb,Cu五个重金属含量（除渝北区外），均在国家土壤环境质量标准内，属自然背景值一级标准。Cd和Zn高于全国土壤中的平均含量和背景值含量，属二级标准。土壤的重金属含量与土壤母质类型，pH值，阳离子交换量，有机质，无定形铁和物理性粘粒有关，同时存在一定的地域分布。重庆近郊的土壤所有重金属含量相对较高。土壤重金属的可给态或有效性含量极低，锌和铜不是过量，而是不足。小麦籽粒中As,Cr,Pb,Zn,Cu含量低于国家食品对重金属限量标准和小麦籽粒背景值标准，Hg,Cd含量高于国家规定标准。籽粒中的Cu,Zn含量是小麦茎叶中的2.0-2.2倍，而茎叶中的Hg,Pb,As,Cr,Cd含量明显高于籽粒。     

母岩的风化剥蚀速率与土壤允许流失量的关系 --以长江三峡坝区风化花岗岩土壤为例

土壤允许流失量的确定是一个非常复杂而又必须解决的问题，它关系到水土保持措施的布设和土壤的可持续利用。然而，发育在不同母质上的土壤，其土壤的最大允许流失量差异很大，确定这一值的依据也各不相同。在岩成土壤地区，母岩风化剥蚀速率的大小直接影响土壤的发育。是确定土壤允许流失量、分析人类加速水土流失的重要依据之一。选长江三峡黄陵背斜段风化花岗岩土壤为研究对象，根据剥蚀沉积相关原理，通过恢复古地理环境及时代，计算出新生代以来本区花岗岩的平均风化剥蚀速率为16．97mm／ka．最大剥蚀速率为49．56。又根据区内太平溪流域的泥沙资料，算出了当地现代的剥蚀速率，多年平均为297．7mm／ka，最小值为31．5mm／ka，而水利部颁布的当地土壤允许流失量为200t／km^2,a，折合为76．9mm／ka，二者相差近1．5—4．5倍。基于此。提出了确定土壤允许流失量必须参考母岩风化剥蚀速率的新观点。     

生态土壤渗滤系统启动周期研究

利用室内模拟试验装置,考察了4种生态土壤渗滤系统在0.1 m3/(m2·d)的水力负荷条件下对生活污水中TP、COD和NH3-N的去除效果及启动周期; 同时对整个系统及同类生态工艺启动周期的判断方法做了探讨.研究结果表明,生态土壤渗滤系统对TP、COD和NH3-N的启动周期分别为15～27 d、24～40 d和24～26 d; 土壤渗滤系统对TP的启动周期最短,对COD的启动周期最长; 处理系统启动周期的判断原则是综合考察系统对主要污染物各自的启动周期,以最长的作为系统启动周期.4组试验中,1#和2#系统的启动周期为40 d; 3#和4#的为24 d.     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。     

人类活动对土壤环境的影响及对策

人类不合理的开发行为给土壤环境带来了沉重的负面影响，主要表现为土壤沙化、土壤侵蚀、土壤盐渍化、土壤污染等。本文以此为出发点展开讨论，分析各种现象的成因，并提出相应对策。