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     

近14年西北地区甲醛柱浓度的时空变化研究

基于臭氧监测仪（OMI）卫星反演数据,对2005~2018年西北4省区域大气甲醛柱浓度数据进行提取及分析,探讨其时空变化特征及影响因素.结果表明：在时间变化上,14a甲醛柱浓度整体呈先上升后下降的波动变化趋势,夏秋季显著高于冬春季,且冬季均值略高于春季.在空间分布上,甲醛柱浓度自西向东、自北向南逐渐升高,高值区集中于陕西和甘肃东南部及青海西南部;低值区集中于宁夏、青海和甘肃的西北部;稳定性呈现出东部分散、西部集聚、差异显著的分布格局.影响甲醛柱浓度变化的因素包括自然和人为因素,自然因素中,甲醛柱浓度受地形影响显著,与风向、气温均呈现显著正相关;人为因素中,甲醛柱浓度与人口密度、地区生产总值、工业废气排放量及建筑房屋竣工面积均表现出正相关关系,与工业废气排放量的相关度最高.大气中甲醛分子与气溶胶粒子二者间呈显著正相关关系,这进一步说明甲醛浓度受到了诸多因素的综合影响,但气溶胶粒子、气温及工业废气的排放是主导因素.     

Role of glycine on sulfuric acid-ammonia clusters formation: Transporter or participator

Glycine(Gly) is ubiquitous in the atmosphere and plays a vital role in new particle formation(NPF).However,the potential mechanism of its on sulfuric acid(SA)-ammonia(A)clusters formation under various atmospheric conditions is still ambiguous.Herein,a(Gly)_x·(SA)_y·(A)_z(z≤x+y≤3) multicomponent system was investigated by using density functional theory(DFT) combined with Atmospheric Cluster Dynamics Code(ACDC) at different temperatures and precursor concentrations.The results show that Gly,with one carboxyl(-COOH) and one amine(-NH_2) group,can interact strongly with SA and A in two directions through hydrogen bonds or proton transfer.Within the relevant range of atmospheric concentrations,Gly can enhance the formation rate of SA-A-based clusters,especially at low temperature,low [SA],and median [A].The enhancement(R) of Gly on NPF can be up to 340 at T=218.15 K,[SA]=10~4,[A]=10~9,and [Gly]=10~7 molecules/cm~3.In addition,the main growth paths of clusters show that Gly molecules participate into cluster formation in the initial stage and eventually leave the cluster by evaporation in subsequent cluster growth at low [Gly],it acts as an important "transporter" to connect the smaller and larger cluster.With the increase of [Gly],it acts as a "participator" directly participating in NPF.     

龙岩市区大气颗粒物中多环芳烃的种类和时空分布特征及来源

采用恒能量同步荧光法检测了龙岩市大气颗粒物样品中的多环芳烃(PAHs),比较了龙岩市区大气颗粒物中多环芳烃含量的差异以及不同季节对多环芳烃含量的影响,讨论了其分布规律及污染源。     

Distribution of airborne particles from multi-emission source

The purpose of this work was to study the distribution of airborne particles in the surroundings of an iron and steel factory in southern Finland. Several sources of particulate emissions are lying side by side, causing heavy dust loading to the environment. This complicated multi-pollutant situation was studied mainly by SEM/EDX methodology.Particles accumulated on Scots pine bark were identified andquantitatively measured according to their element content,size and shape. As a result, distribution maps of particulateelements were drawn and the amount of different particle typesalong the study lines was plotted. Particulate emissions fromthe industrial or energy production processes were not themain dust source. Most emissions were produced from theclinker crusher. Numerous stockpiles of the industrial wastesand raw materials also gave rise to particulate emissions as aresult of wind erosion. It was concluded that SEM/EDXmethodology is a useful tool for studying the distribution ofparticulate pollutants.     

空气细颗粒物(PM2.5)污染特征及其毒性机制的研究进展

细颗粒物(PM2.5)是指空气动力学直径≤2.5μm的颗粒物,其表面吸附大量的有毒有害物质,并可通过呼吸沉积在肺泡,甚至可通过肺换气到达其他器官.由于细颗粒物的重要性,美国EPA已经于1997年颁布了细颗粒物的空气质量标准,年均值为0.015mg/m3,日均值为0.065mg/m3,然而我国至今仍未制定细颗粒物空气质量标准.颗粒物上吸附的化学组分主要可分成自然来源及燃煤或燃油等人为污染来源两大类,特别是来自工业性和居住区燃煤及汽车燃油尾气.空气细颗粒物污染表现为形态各异、成分复杂等特征.细颗粒物有明显的毒性作用,可引起机体呼吸系统、免疫系统等较为广泛的损害.细颗粒物与心肺疾病密切相关,如增加入院率、急诊次数、呼吸疾病及症状增加、肺功能下降,甚至于过早死亡.简要概述了细颗粒物的污染特征及其毒性机制研究进展.     

大气污染物影响因素的灰色关联分析

运用灰色系统理论，对产生和影响城市大气主要污染物的相关因素，利用灰色关联分析方法进行了量化分析研究，根据研究结果，提出了控制大气污染的防治对策．     

同位素方法在大气甲烷研究中的应用

通过对大气甲烷研究的同位素方法理论基础及其研究进展的综述，概括介绍了现有的大气甲烷同位素研究方法和所取得的成果，讨论分析了在中国开展该项研究的意义和前景。     

太原市工业区大气中TSP浓度及元素成分分析

采用校正空白称量法对太原市工业区大气中ＴＳＰ浓度进行了测定分析，对该区大气ＴＳＰ浓度随时间变化的规律，超标情况及污染特征进行了研究，同时测定了ＴＳＰ中Ｃｒ、Ｐｂ等１２种元素的含量。     

主成份分析法在大气环境质量综合评价中的应用

介绍了主成份分析法评价大气环境质量的基本原理，并对某市的大气环境质量进行了综合评价。最后，与其它方法的评价结果进行了对比分析，进一步证实了主成份分析法的科学性、合理性。