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     

Acid Deposition in the Tuscan Appennines During the Dry Period 1988-89

The typical parameters of acid precipitation are evaluated in the forest of Vallombrosa (Tuscan Appennines) during the dry period 1988-89. Individual rain events (dry and wet deposition) were sampled in a clearing of the forest and below the canopy of an evergreen tree as well as a deciduous broadleaf tree.

In atmospheric precipitation the pH values usually vary around 4.4, with neutralization in the hot season due to calcareous material from distant sources. Relatively large concentrations of Pb and Cd are found in rain, but only in a small amount in canopy leachate. Aluminium, manganese and iron are more significantly washed off than Pb and Cd.     

高镁铝合金在喷射成形过程中显微组织的变化

研究了高镁铝合金在喷射成形过程中显微组织的变化。沉积态高镁铝合金基体呈全部等轴晶组织并存在少量显微孔洞是沉积态组织的主要特征。分析了等轴晶组织和显微孔洞在喷射成形中生成的机制。     

Occurence and Distribution of Polycyclic Aromatic Hydrocarbons in Ankara Precipitation

Urban atmospheric environment contains many trace organic pollutants that are related to the incomplete fuel combustion in domestic heating, industrial plants and automobile traffic. Removal of these pollutants from the atmosphere takes place through wet and dry deposition as well as chemical transformations. In this study, concentrations of polycyclic aromatic hydrocarbons (PAHs) in wet deposition samples were determined at an urban site of Turkey. Wet and dry deposition samples were collected using Andersen Rain Sampler. The sampler was modified accordingly for the collection of organic pollutants. Collected samples were preconcentrated by using solid phase extraction (SPE) disks and consecutively analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). Among the 13 compounds quantified in this study, anthracene, fluoranthene, and pyrene were found more frequently and at elevated concentrations (202, 271 and 260 ng L^-1 mean concentrations, respectively).Concentrations of PAHs were found to be high in winter period.     

Modelling nitrogen fluxes at the landscape scale

The distribution and impacts of different nitrogen pollutants are inextricably linked. To understand the problem fully, the interactions between the different pollutants need to be taken into account. This is particularly important when it comes to abatement techniques, since measures to reduce emissions of one nitrogen pollutant can often lead to an increase in another. This project represents a step towards greater understanding of these issues by linking together new and existing nitrogen flux models into a larger framework. The modelling framework has been constructed and some of the nitrogen flows between fields, farms and the atmosphere have been modelled for a UK study area for typical farm management scenarios.     

Applying metabolic fingerprinting to ecology: The use of Fourier-transform infrared spectroscopy for the rapid screening of plant responses to N deposition

The potential for metabolic fingerprinting via Fourier-transform infrared (FT-IR) spectroscopy to provide a novel approach for the detection of plant biochemical responses to N deposition is examined. An example of spectral analysis using shoot samples taken from an open top chamber (OTC) experiment simulating wet ammonium deposition is given. Sample preparation involved oven drying and homogenisation via mill grinding. Slurries of a consistent dilution were then prepared prior to FT-IR analysis. Spectra from control, 8 and 16 kg N ha^–1 yr^–1 treatments were then subjected to cross-validated discriminant function analysis. Ordination diagrams showed clear separation between the three N treatments examined. The potential for using Calluna vulgaris (L.) Hull as a bioindicator of N deposition is further evident from these results. The results also clearly demonstrate the power of FT-IR in discriminating between subtle phenotypic alterations in overall plant biochemistry as affected by ammonium pollution.     

Long range trans-Pacific transport and deposition of Asian dust aerosols

The deposition of Asian dust aerosols during their trails-Pacific Uansport might cause significant marine phytoplankton biomass increases.However,the knowledge of the trans-Pacific dust transport,deposition,and spatial distribution is still poor due to a lack of continuous and simultaneous observations in the Asian subcontinent,the north Pacific Ocean,and North America.The severe Asian dust storm during 6 to 9 April 2001 provided an opportunity to gain a better understanding of trans-Pacific dust transport and deposition,using a comprehensive set of observations from satellites,ground-based light detection and ranging,aircraft,and surface observation networks.The observations and model simulations outline the general pattern of dust transport,deposition,vertical profile,and spatial distribution.The following points were observed(1)the surface dust concentrations decreased exponentially with the increasing dust transport distance from 80°E to 120°W along the transport pathway;(2)the altitude of the dust concentration peak increased with increasing transport distance in the north Pacific region;and (3) the spatial distribution of dust deposition mainly depended on the trans-Pacific transport route.     

大气环境数据分析预测方法对比研究

以西安市2006年9月27日至2008年5月3日每日的SO2平均浓度时间序列为例,应用时间序列分析对前555个数据进行拟合,得到合适的时间序列模型ARIMA(1,1,2);利用神经网络中的BP神经网络和RBF神经网络对同样的样本进行训练,用这三种方法对2008年4月4日至2008年5月3日的SO2日均浓度值进行了预测,并用同样的方法分析预测了同期PM10日均浓度值,最后比较了它们的预测效果。结果表明,利用这三种方法进行浓度预测都是可行的,其中RBF神经网络法的预测误差最小,效果最好。     

镇江市大气环境承载力研究

根据前人对大气环境容量和环境承载力计算的对比分析,计算2012年镇江市的大气环境容量和大气环境承载力指数,通过对该市的气象条件和地理位置的分析,选取SO_2、NO_x和PM_(10)这3种主要大气污染物,并分析其环境承载状况。结果表明:句容市、丹阳市、杨中市处于高承载的状态,临界超载、严重超载和超载的3个区分别是润州区、京口区和镇江新区,针对这3个区提出相应改进措施。     

珠江口无机氮湿沉降规律及大气输送的研究

针对2007年3～11月广东中山市横门站的降水资料,分析了珠江口氮湿沉降特征及其来源.结果显示:研究期间横门降水中NH+4-N和NO-3-N的降雨量加权平均浓度分别为0.62和0.41mg·L-1;其季节变化规律表现为秋季最高,其次是春季,夏季最低.降水NH+4-N和NO-3-N的浓度呈显著正相关,与降水pH值呈负相关.利用气团轨迹后推以及天气形势得出,横门陆地性降水氮浓度最高,海洋性降水氮沉降通量最高.云下气团分类结果表明,海洋性NE类气团对横门无机氮湿沉降的输送负荷最大.