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1.
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  相似文献   
2.
选择位于红壤丘陵区的鄱阳湖流域作为研究对象,利用1 km×1 km分辨率的时序SPOT4 VEGETATION数据,对流域内典型土地覆被--常绿覆被的绿度值、峰值、谷值、年均NDVI(NDVI-I)和NDVI年内极差(NDVI MM)等特征值进行了提取。在此基础上,探讨了不同常绿覆被类型的NDVI指数年内季节变化规律。结果表明:时序NDVI指数基本上能够较好地刻画不同常绿覆被类型之间的差异性,植被指数NDVI特征值随覆被的类型及其生长状态有规律地变化,即NDVI年均值和最小值基本上按“常绿阔叶林>常绿针阔叶混交林>常绿针叶林>常绿针叶-落叶混交林”的顺序变化;典型常绿阔叶林的NDVI指数年内变化曲线基本上没有大的起伏波动;常绿针叶林以及常绿针阔叶混交林占主导地位的常绿混交林NDVI指数年内变化比较和缓,但常在8月和11月有所波动;以常绿针叶林为主、但有较多落〖JP2〗叶林混杂其中的常绿混交林,其NDVI指数年内变化曲线基本上呈和缓的单峰型波动。  相似文献   
3.
北京南部城区PM2.5中碳质组分特征   总被引:5,自引:3,他引:2  
为了解《大气污染防治行动计划》实施后北京市大气PM2.5中碳质组分特征,于2017年12月至2018年12月在北京污染较重的南部城区进行了PM2.5连续采样,对其中的有机碳(OC)和元素碳(EC)进行了全面研究.结果表明,北京大气PM2.5、OC和EC浓度变化范围分别为4.2~366.3、0.9~74.5和0.0~5.5 μg ·m-3,平均浓度分别为(77.1±52.1)、(11.2±7.8)和(1.2±0.8)μg ·m-3,碳质组分(OC和EC)整体占PM2.5的16.1%.OC质量浓度季节特征表现为:冬季[(13.8±8.7)μg ·m-3] > 春季[(12.7±9.6)μg ·m-3] > 秋季[(11.8±6.2)μg ·m-3] > 夏季[(6.5±2.1)μg ·m-3],EC四季质量浓度水平均较低,范围为0.8~1.5 μg ·m-3.二次有机碳(SOC)年均质量浓度为(5.4±5.8)μg ·m-3,四季贡献比例范围为45.7%~52.3%,年均贡献为48.2%,凸显了二次形成的重要贡献.随污染加重,尽管OC和EC贡献比例均降低,但浓度水平却成倍升高,OC和EC浓度在严重污染天分别是空气质量为优天的6.3和3.2倍.与非供暖时段相比,供暖时段PM2.5、OC和SOC浓度分别增加了14.4%、47.9%和72.1%,体现了OC对供暖季PM2.5污染的重要贡献.PSCF分析表明,位于北京西南的山西省和河南省部分区域是PM2.5和OC的主要潜在源区,且PM2.5潜在源区更为集中;EC的PSCF高值(>0.7)区域较少,主要位于北京南部,如山东省和河南省部分地区,且北京市及周边地区贡献明显.  相似文献   
4.
保定市大气污染特征和潜在输送源分析   总被引:1,自引:0,他引:1       下载免费PDF全文
保定市是京津冀地区重要城市之一.为了解保定市大气污染物质量浓度特征和潜在输送源,对保定市国控点2017年1月1日-12月31日PM10、PM2.5、SO2、NO2、O3、CO等常规大气污染物数据进行分析,并利用TrajStat后向轨迹模型进行区域传输研究.结果表明:①ρ(PM10)、ρ(PM2.5)、ρ(SO2)、ρ(NO2)分别为(138±96)(84±66)(29±23)和(50±24)μg/m3,与2016年相比分别下降5.9%、9.1%、25.5%和13.1%;ρ(CO)较2016年下降了14.0%;ρ(O3)较2016年增长了25.2%.ρ(PM10)、ρ(PM2.5)、ρ(NO2)和ρ(O3)分别超过GB 3095-2012《环境空气质量标准》二级标准限值的0.97、1.40、0.25和0.34倍,ρ(SO2)和ρ(CO)未超标.②除ρ(O3)外,其他污染物质量浓度均呈冬季最高、夏季最低的季节性特征,其中,冬季PM2.5污染最为严重,春季PM2.5~10(粗颗粒物)污染严重.③空气质量模型源解析结果显示,保定市ρ(PM2.5)约60.0%~70.0%来自本地污染源排放.后向轨迹结果表明,在外来区域传输影响中,保定市主要受到西北方向气团(占比为21.7%~60.0%)远距离传输和正南方向气团(占比为34.8%~50.5%)近距离传输的影响.④PSCF(潜在源贡献因子分析法)和CWT(浓度权重轨迹分析法)分析表明,除保定市及周边区县本地污染贡献外,位于太行山东麓沿线西南传输通道的邯郸市、邢台市、石家庄市是影响保定市PM2.5的主要潜在源区.研究显示,PM2.5为保定市大气中的主要污染物,并呈冬季高、夏季低的变化特征,其主要来自西北远距离输送和南部近距离传输.   相似文献   
5.
Review on the annual PM10 concentrations over a 10-year period shows that Macau is subjected to severe fine particulate pollution. Investigations of its variation in monthly and daily time scales with the local meteorological records reveal further details. It is found that a distinct feature of the Asian monsoon climates, the changes of wind direction, mainly controls the general trend of PM10 concentration in a year. The monsoon driven winter north-easterly winds bring upon Macau dry and particle enriched air masses leading to a higher concentration in that period while the summer south-westerly winds transport humid and cleaner air to the region leading to a lower PM10 value. This distinct seasonal feature is further enhanced by the lower rainfall volume and frequency as well as mixing height in winter and their higher counterparts in summer. It is also found that the development of tropical cyclones near Macau could also impose episode like PM10 concentration spikes due to the pre-typhoon induced stagnant air motion followed by the swing of wind direction to the northerly.  相似文献   
6.
Continuous visibility monitoring has been carried out inKwangju, Korea since May 1999. The total light extinctioncoefficient b ext measured by a transmissometer andreveals seasonal trends in urban visual air quality,especially under hazy conditions with a visual range of lessthan 15 km. Seasonal atmospheric visibility under lowrelative humidity during the winter was observed to be betterthan during any other seasons. Summertime visibility wasseverely degraded due to highly increased light scattering byhygroscopic particles under high humidity atmosphericconditions. Visibility during spring and fall was alsomoderate. However, yellow sand in spring caused the lowestvisibility conditions over the measurement area for a fewdays. With continuous monitoring using the transmissometer,the daily average seasonal visual range was measured to be13.1, 9.2, 11.0, and 13.9 km in spring, summer, falland winter, respectively. Under the atmospheric humiditycondition less than 60%, visual range was observed tobe 16.1, 13.9, 15.1, and 16.6 km in spring, summer,fall, and winter, respectively. The mean light extinctionbudget by sulfate and nitrate aerosols was determined to bethe highest value of 63.71% during the summer and thelowest value of 27.08% during spring. During the `yellow sand dust' period, a mean light extinction budget by soil particles was estimated to be at an unusually high value of 44.22%.  相似文献   
7.
This article presents and discusses SO2 (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO2 measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO2 concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO2 average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO2 reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.  相似文献   
8.
天山云杉天然林分土壤呼吸速率的时空变化规律分析   总被引:1,自引:0,他引:1  
天山云杉(Picea schrenkiana var.tianschanica(Rupr.)Chen et Fu)是构成天山山地森林生态系统的主体。在天山中部,从天山云杉在此区域分布的底线开始,结合天山云杉自然分布特征,沿每隔约100m的海拔梯度选择典型地段设置样地。根据远红外气体分析原理,采用LI-6400-09土壤呼吸室和LI-6400便携式光合作用测量系统,于2006年6-9月,测定了天山云杉天然林分在生长季内土壤呼吸速率随海拔高度和时间的变化规律。在空间上,林分的土壤呼吸速率并非随海拔高度呈线性增加或减少的关系,而是有规律的波动,在海拔1950~2110m之间,土壤呼吸速率是随着海拔高度的增加而降低,在2110~2428m之间是随着海拔高度的增加而升高,在海拔2428m处达到最大的呼吸速率值后又降低。不同海拔高度林分的土壤呼吸速率主要受土壤表面空气相对湿度及土壤温度的影响。在时间上,林分的土壤呼吸速率在生长季内随不同月份的变化为单峰曲线,其最大值出现在7月份;生长季内土壤呼吸速率与土壤温度呈显著负相关,与土壤表面空气相对湿度呈极显著正相关。而林分土壤呼吸速率的日变化在各时间点上的大小排序为7月>6月>8月>9月。它的变化与土壤温度具有极显著的正相关性,与土壤表面空气相对湿度具有显著的负相关性。  相似文献   
9.
不同基质垂直流人工湿地对猪场污水季节性处理效果的研究   总被引:16,自引:0,他引:16  
研究了3套不同基质垂直流人工湿地小试装置在不同季节处理猪场污水的运行效果.结果表明,垂直流人工湿地对有机污染物的去除效果随季节变化差异不明显,对有机物降解情况可用一级降解模型模拟;传统型湿地系统NH4 -N去除率在各季节稳定在52%,而沸石和沸石-煤渣型系统冬季NH4 -N去除效率分别从秋季的89.8%和93.4%下降至冬季的64.2%和73.5%,春、夏季回升至80%左右.冬季湿地系统中生物硝化与反硝化作用的减弱影响了垂直流人工湿地系统TN的去除;3套不同基质系统中,沸石-煤渣型系统各高度层硝化强度均为最高,沸石型和沸石-煤渣型系统的反硝化强度明显高于传统型系统,与实际运行过程TN去除率变化相吻合.采用沸石作为基质有利于系统的反硝化进程和TN的去除.垂直流系统对TP去除率随季节性变化波动不显著,但随着垂直流人工湿地系统的运行,基质层对TP的吸附逐渐饱和,去除效率明显下降.  相似文献   
10.
广州大田山垃圾填埋场空气中微量挥发有机污染物组成   总被引:9,自引:1,他引:9  
以广州大田山垃圾填埋场为例,研究了在不同季节填埋场空气中微量挥发性有机污染物的种类和含量变化情况。结果表明,在春、夏季样品中可分别检测出47和64种化合物,其中有些化合物为USEPA优先控制毒害有机污染物;夏季样品中微量挥发性有机污染物的浓度大多比春季样品高,有的甚至高1个数量级以上。因此加强对垃圾的卫生填埋,尤其是加强对夏季的垃圾卫生填埋的科学管理,减少挥发性有机污染物向大气中的扩散,应给予充分的关注。  相似文献   
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