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     

Fluctuations of Population Size and Structure in the Northern Mole Vole: Preliminary Analysis

Long-term stationary studies on the ecology of the northern mole vole (Ellobius talpinus Pall.), performed by the mark–recapture method from 1985 to 1997, have provided original data on population dynamics and structure. The analysis shows that, to reveal cyclic fluctuations of population size in this species, the period of three years should be taken as a unit of time for estimating the duration of one phase. The 12-year population cycle in E. talpinus has four distinct phases: an increase, a peak, a decline, and a minimum. At each phase, the population is characterized by certain features of family structure, age composition, birth and death rates, and the composition of migrants.     

淹水时间对土壤粘闭的影响

本文研究了植稻前淹水时间长短对土壤物理性质和粘闭作用的影响。结果表明,淹水可以显著地降低土壤强度,但土壤抗穿透力并不随淹水时间的延长而进一步明显下降;延长淹水时间,可以促进土壤粉粒和粘粒的分散,但土壤粘闭胼形成的有效粘闭层厚度以及粘闭后表层土壤强度的降低、主要受所使用的粘闭机具的影响,而与淹水时间的长短无关。因此,过分地延长淹水时间的措施,在生产实践上的意义并不大。     

京津冀西北典型流域地下水化学特征及补给源分析

为揭示京津冀西北典型流域地下水循环特征,运用环境同位素和水化学技术等方法分析张家口市不同流域水体氢氧同位素特征、水化学特征及时空变化特征、地表地下水转化关系。结果表明：地表水化学类型主要为HCO₃-Mg·Na和HCO₃·Cl-Na型;地下水化学类型不同时期表现出不同的类型,水化学类型更为多样,主要以HCO₃-Mg·Na型、HCO₃·Cl-Na型、HCO₃·Cl-Na·Mg为主。地表河水和地下水中离子均主要来源于岩石风化作用;张北和桑干河流域地下水中离子偏向于蒸发浓缩作用控制。张家口市各流域地表地下水δ¹⁸O、δD组成较为接近,表明了当地地表水和地下水均受到大气降水的补给。大气降水和地表河水对地下水的补给比例均值分别为37.74%和62.26%,以地表河水的补给为主要方式。     

大兴安岭5种乔木树种燃烧释放PM2.5中水溶性元素特性

采用自主设计的生物质燃烧实验装置,在不同燃烧状态（明燃、阴燃）下,对大兴安岭林区5种典型乔木树种的不同部位（枝、叶、皮）燃烧释放PM_2.5中的水溶性元素特性进行研究.结果显示,不同树种间PM_2.5的排放因子差异显著,排放范围为（2.408±0.854）~（9.227±1.172）g/kg.5种乔木树种燃烧释放PM_2.5中主要检测到Mg、Ca、K等16 种元素,其中Ca、K、Zn、Mg 4种元素的排放因子明显大于其它元素.不同树种间元素排放因子差异较大,针叶树的排放因子一般高于阔叶树.除Cd元素外,不同器官间排放的元素总量无明显差异.不同树种不同器官燃烧释放PM_2.5中水溶性元素的占比顺序较为一致,其中Ca、K、Zn和Mg 4种元素的排放因子在枝、叶、皮中均较高.此外,燃烧状态对元素排放特征影响较大,Li、Mg、Ca等7种元素的排放因子均表现为明燃显著高于阴燃.     

不同区域城市空气O3和PM2.5累积速率时序模型

利用2017—2018年全国7个区域10个典型城市环境空气O₃和PM_2.5浓度数据，统计污染物累积速率，进而采用回归方法拟合污染物浓度及其累积速率的时间序列模型，分析不同区域污染物时序变化特征差异。结果表明：不同区域O₃浓度时序曲线拟合程度总体高于PM_2.5，石家庄O₃拟合程度最高，西安PM_2.5拟合程度最高。以07：00、14：00分别作为O₃、PM_2.5模拟起点是24 h中的最优模型。不同城市夏季O₃小时浓度时序变化曲线均为单峰形态，O₃浓度及累积速率峰值出现时间可能由城市所处经度决定，太原O₃累积最快，西安O₃消解最快。各城市间冬季PM_2.5小时浓度及其累积速率时序变化曲线形态差异较大，沈阳PM_2.5累积和消解均最快。与浓度相比，城市环境空气O₃和PM_2.5累积速率与光照、扩散条件等有更好的时间相关性。     

地表水样品自然沉降时间对总磷测定结果的影响分析

地表水中总磷含量高低是评定水质优劣的一项重要指标,分析数据表明丰水期中总磷主要来源于泥沙中吸附的有机磷和无机磷,而溶解态磷含量较少;水样中总磷含量随着自然沉降时间的延长而逐渐降低.因此样品采集回来后样品的自然沉降时间是影响地表水中总磷测定结果的一个主要原因之一.     

同时分解法测定水中总氮和总磷

通过实验找到了同时测定水中总氮和总磷的条件,实现了总氮和总磷的同时测定。     

4类噪声标准适用区最佳监测时间研究

以1年的实测数据为分析样本,分别采用误差理论分析及数理统计分析方法,在保证一定精确度前提下确定出反映4类标准适用区噪声水平的最佳监测时间。     

城市空气质量日报自动发布系统的研究与开发

详细介绍了“城市空气质量日报自动发布系统”的开发背景和开发过程 ,并对系统整体的架构和所用到的技术作了针对性的说明 ,阐明了作者对此类系统的前景和发展方向的看法。