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     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

Impact of continental margins in the Mediterranean Sea: Hints from the surface colour and temperature historical record

The surface colour and temperature fields of the Mediterranean Sea, as appearing in time series, of basin-wide images available in the CZCS (1979–1985) and AVHRR (1982–1991) historical archives, differentiate between basin interior and continental margins affected by coastal patterns, river plumes, and mesoscale features. The original data were processed to apply calibration factors, to correct for atmospheric contamination, and to estimate chlorophyll-like pigment concentration and surface temperature. Composites were derived, as monthly and annual means, using a fixed equal-area projection with a 1-km² pixel grid. Enhanced pigment values and lower temperatures along the northern coastal areas (i.e. the Ligurian, Provençal and Balearic basins, as well as the Adriatic, and Aegean Seas) have been associated with the impact of runoff from continental margins (i.e. both a direct impact due to the sediment load and one induced on the planktonic flora by the associated nutrient load) and with vertical mixing due to the prevailing winds (i.e. the Mistral in the northwest, the Bora in the Adriatic, the Etesians in the Aegean). The pattern of increasing pigments and decreasing temperatures in seen to develop in the monthly images from the coastal zone towards the open sea from summer to winter, and then back from winter to summer. The southern coastal areas show different values, namely lower pigments and higher temperatures (except in areas where the data are altered by signal contamination). It is suggested that differences in geomorphology and meteorology of the basin margins have an impact on both water biogeochemistry and dynamics, influencing the biooptical and thermal properties of the various sub-basins, and of the entire Mediterranean region.     

从环境立法进程展望中国大气污染防治战略的发展方向2002年9月12日在能源与环境中美研讨会上的讲话

本文从中国环境立法，特别是再次修改《大气污染防治法》等展望中国大气污染防治的重要战略方向。     

海洋硫酸盐还原菌群处理烟气脱硫废水

针对高盐硫酸根废水的特性,从海底沉积物中富集得到1个硫酸盐还原菌菌群SRB-2,并研究了盐度、温度、pH值、碳源、硫酸根浓度和铁形态对其活性的影响.结果表明,SRB-2为嗜盐中温硫酸盐还原菌群, 可以利用乙醇及乳酸为单一碳源,最佳生长温度为30～40℃,最佳生长pH值为7.4～8.3,SRB-2菌群能够在硫酸根浓度为5 200 mg/L或盐度为60　g/L的条件下正常生长,还原铁粉对该菌群还原硫酸根的能力具有加强作用,而二价铁离子则抑制细菌活性.扫描电子显微镜及光学显微镜对菌体形态研究发现,在反应器填料表面,该菌群中有大量短竿状及螺旋状细菌黏附,而在底部,主要为表面覆盖大量黑色粘稠物质,由短竿状细菌组成,推测其可能是菌种SRB-2-64（GenBank 序列号：EU167911）的堆积.     

基于灰色聚类法的地铁运营安全趋势分析

为评估地铁运营安全水平,掌握地铁运营风险变化趋势,采用灰色聚类法对某地铁线路运营一年以来每个月份的安全水平进行了分级评价。选取对地铁日常运营具有重要影响的设备设施故障作为评价指标,评价方法挖掘地铁运营以来的历史数据信息,体现了设备设施故障变化的时间特性,减少了安全评价中的主观性。将地铁运营安全水平分为五个安全等级,选取15%、35%、50%、65%、85%作为各安全等级的累积百分频率特征点,建立白化权函数得到各评价指标的灰类白化值。结合各设备设施的指标权重,得到了地铁线路运营一年来每个月份的安全等级情况。该方法为分析地铁运营安全趋势提供了参考。     

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。     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

克山县空气质量及变化趋势

通过对克山县2003—2012年的空气监测数据分析,二氧化硫和总悬浮物颗粒物呈下降趋势,氮氧化物和降尘浓度变化不大;尘类是影响环境质量的主要污染物,县区环境空气质量呈轻度污染,根据各年度的监测数据来看,环境空气质量逐年得到改善。