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     

HEAVY RAINFALL DISTRIBUTIONS BY SEASON IN LOUISIANA: SYNOPTIC INTERPRETATIONS AND QUANTILE ESTIMATES1

ABSTRACT: In most studies, quantile estimates of extreme 24-hour rainfall are given in annual probabilities. The probability of experiencing an excessive storm event, however, differs throughout the year. As a result, this paper explored the differences between heavy rainfall distributions by season in Louisiana. It was concluded by using the Kruskal-Wallis and Mann-Whitney tests that the distribution of heavy rainfall events differs significantly between particular seasons at the sites near the Gulf Coast. Furthermore, seasonal frequency curves varied dramatically at the four sites examined. Mixed distributions within these data were not found to be problematic, but the mechanisms that produced the events were found to change seasonally. Extreme heavy rainfall events in winter and spring were primarily generated by frontal weather systems, while summer and fall events had high proportions of events produced by tropical disturbances and airmass (free-convective) conditions.     

Analysis of Roadside Inhalable Particulate Matter (PM10) in Major Korean Cities

A data analysis of three major Korean cities was conducted to assess roadside inhalable particulate matter 10 μm or smaller in aerodynamic diameter (PM₁₀), including temporal and meteorological variations, over a recent period of 4 to 6 years. The yearly roadside PM₁₀ concentrations presented a well-defined increasing trend or no trend depending on the roadside monitoring station. Most mean values exceeded or approximated the Korean standard of 70 μg/m³ per year for PM₁₀. A representative roadside diurnal trend was characterized by a distinct morning maximum. In most cases, the Sunday roadside concentrations were similar to or somewhat lower than the weekday concentrations, and the PM₁₀ concentrations presented a well-defined seasonal variation, with the maximum concentration in March. The monthly maximum concentrations observed in March were most likely attributable to Asian dust storms. In two metropolitan cities (Seoul and Busan), the frequency of days with roadside PM₁₀ concentrations exceeding the standard of 150μg/m³ per 24 h was much lower for the roadside monitoring stations than for the residential monitoring station, whereas in the third city (Daegu), this result was reversed. Interestingly, the average maximum concentrations observed for the roadside sites in Seoul and Busan during March were higher than those for the residential sites, suggesting that the roadside concentrations responded more to the dust storms than the residential areas. The relationship between the pollutant concentrations and five important meteorological parameters (solar radiation, wind speed, air temperature, relative humidity, and precipitation) showed that the number and type of meteorological variables included in the equations varied according to the monitoring station or season. Finally, the current results confirmed that attention should be given to the PM₁₀ exposure of residents living near roadways.     

Trends in airborne particulates in Stuttgart, Germany: 1972-2005

Since 1972, at the University of Hohenheim in Stuttgart, Germany, airborne particulate matter (PM12 and then PM10) was continuously collected on filters and analyzed for environmentally relevant elements by X-ray fluorescence analysis. The resulting long-term time series are suitable for the investigation of trends and of seasonal variation. For the period 1972-2005, monthly and annual concentration mean values of 13 elements (Br, Ca, Cr, Cu, Fe, K, Mn, Ni, Pb, S, Ti, V, and Zn) in the air are presented. Trend curves were fitted and the mean yearly variation of the concentration for these elements was calculated and represented graphically. All trend curves show a diminution of the air pollution during this period, but to different extents. Mean trends in percent per year were calculated for each element both for the entire investigation period and for three data subsets of 10-11 years. Possible explanations are discussed in detail.     

南黄海东部海域浮游生态系统要素季节变化的模拟研究

利用海洋生态系统动力学垂直一维物理-生物耦合模式模拟研究了南黄海东部海域浮游生态系统要素垂直分布的季节变化.物理亚模型为一维POM模式(Princeton Ocean Model),基于文献结果对垂直混合系数Kh和Km进行了调整;生态亚模型为ERSEM模式(European Regional Sea Ecosystem Model),主要考虑浮游植物、浮游动物、细菌、底栖碎屑和营养盐(氮、磷、硅)等状态变量.模拟结果表明,浮游植物出现一年双峰的态势和夏季次表层叶绿素最大值的现象,春、秋季水华期间,表层叶绿素峰值分别为3.25 mg/m3和0.71 mg/m3.浮游动物和细菌在春季水华后表层出现峰值,分别为143.6 mg C/m3和23.55 mg C/m3.硝酸盐、磷酸盐和硅酸盐的垂直分布均在5-11月呈现表层浓度低、底层浓度高的分布.通过计算碳通量可以看出,在春、夏季,浮游植物对无机碳的摄取量分别为58.944 g C·m-2·quarter-1和68.276 g C·m-2·quarter-1,高于细菌对非生命有机碳的摄取.在冬季,细菌对非生命有机碳的摄取超过浮游植物对无机碳的摄取量.浮游动物在冬季主要摄食细菌,占71%;春、夏季主要摄食浮游植物,可达67.5%.浮游植物对碳的释放主要是以DOC的形式,约占90%.     

小流域土地利用结构对氮素输出的影响

以丹江口库区的胡家山小流域为研究区,以资源二号卫星影像图为底图,通过实地调查获取胡家山小流域土地利用图,利用ArcGIS的水文模拟、空间分析模块提取15个集水区,并分析其土地利用结构.根据2008年1～12月各个集水区的出口的总氮、硝态氮浓度的监测数据,定量地分析土地利用结构对氮素输出时空变化的影响.结果表明,胡家山小流域内旱地、居民地对氮素输出起显著源作用,与TN、NO-3-N的Pearson相关系数分别为0.869、0.856和0.826、0.867.林地、疏林地、草地等对氮素输出起汇作用,其中林地、草地汇作用显著,与TN、NO-3-N的Pearson相关系数分别为-0.820、-0.851和-0.602、-0.518.土地利用结构是氮素输出空间变化的关键因素,土地利用类型的空间分布使得汇土地利用类型旱地、居民地对小流域氮素输出影响最大;在不同时间尺度上,土地利用结构对氮素输出浓度影响有所不同.年度上,对氮素输出影响最大的是旱地,季节上,春、夏、秋、冬四季对氮素输出影响最大的分别是旱地、居民地、居民地、旱地;土地利用结构对氮素输出浓度的影响受到降雨、气温、人为等因素的作用.     

崇明东滩不同部位的季节性沉积研究

2002年4月至2003年4月,通过对崇明东滩南部、中部和北部的标志桩观测以及实地观测分析,发现崇明东滩在一年中不同季节冲淤变化过程存在很大差异：春季到夏季,南部以冲刷为主,中部和北部以淤积为主;夏季到秋季,南部和中部以淤积为主,北部表现为冲刷;秋季到冬季,南部、中部和北部都以冲刷为主;头一年冬季到次年春季,南部和北部以淤积为主,中部则表现为冲刷。在同一观测路线上,不同季节高、中、低潮滩冲淤也存在一定差异。通过对沉积物粒度、水体含沙量等指标的测试,并借助潮差等资料,探究了影响潮滩季节性沉积的因素,发现潮滩季节性沉积与潮滩基础地貌、水体含沙量、水动力、潮流等有密切关系;但在不同部位不同季节,各因素对潮滩冲淤影响程度各不相同。     

城郊农业区小流域土地利用结构对氮素输出的影响

以位于湖南省长沙市城郊农业区的金脱河流域为研究区域,通过解译2009年的Spot-5卫星遥感图获取了小流域的土地利用图;结合流域的DEM图,利用ArcGIS 9.3的水文、空间分析模块将流域划分为若干个子流域,分析各子流域的土地利用结构.从2009年12月～2010年11月在各子流域出口处采取水样,分析其TN、NH4+-N、NO3--N输出浓度、输出量的时空变化特征以及与土地利用结构、施肥等因素之间的关系.结果表明,流域径流氮素污染严重,其TN、NH4+-N输出浓度呈明显的季节变化特征,为冬季>春季>夏、秋季,而NO3--N的输出浓度的季节差异较小.流域内的土地利用结构对NO3--N的输出浓度起着重要的控制作用,林地、水面表现为源作用,水田、旱地、居民地为汇作用;不同的时间尺度上土地利用结构对其影响不同,年度尺度上对NO3--N输出影响最大的为旱地,春夏季为林地,秋冬季为旱地.TN、NH4+-N的输出浓度与土地利用结构的相关性较差,各形态氮素的输出量与纯氮施用量、人口数、养猪量表现为极显著正相关.     

北京城区大气干沉降的水溶性离子特征

为了解北京城区大气干沉降中水溶性离子的化学组成与时间变化特征,连续进行了4年多的干沉降采样与分析.结果表明,在222个有效干沉降样品中,存在不同程度的阴离子缺失. SO42-与Ca2+分别是含量最丰富的阴、阳离子组分,其次是NO3-和NH4+. SO42-、NO3-和NH4+呈现相似的季节变化特征,即其浓度在夏季最高,冬季最低. 干沉降基本呈中性,其pH值月变化幅度小,但季节变化明显,夏季低而春季高.     

季节性Kendall检验分析湘江长沙段水质变化趋势

季节性Kendall检验是一种广泛应用于河流水质变化趋势分析的非参数检验。以湘江长沙段三汊矶断面2001—2011年水质监测结果为样本,运用季节性Kendall检验分析湘江长沙段水质变化趋势及影响因素,结果表明:氨氮浓度呈显著上升趋势,总磷浓度呈高度显著上升趋势,总镉、总砷浓度呈高度显著下降趋势,湘江长沙段水质主要受城市生活、工业和农业面源污染物排放的影响,河水流量对水质的影响相对较小。