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     

滤膜法测定空气中氟化物的改进

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浅析分布式防火墙技术

随着计算机网络的不断发展,现有的防火墙体系已不能满足要求,发展新的网络防火墙技术已非常重要.分布式防火墙具有明显的防护优势,了解分布式防火墙技术,并在实际应Ζ用中用好它,已成为保障我们网络安全的必要.     

净化SO2的生物膜填料塔中微生物类群分析

对净化废气中SO2的生物膜填料塔内的微生物进行了分离纯化并做鉴定,得到一株嗜酸性氧化硫硫杆菌（Acidithiobacillus thiooxidans IEL001）和一株分类地位非常接近链二孢属（Bispora sp.）的极端嗜酸真菌IEL002,生物膜填料塔内的极端酸性环境和有机营养的缺乏导致生物膜上的微生物种类较为单一,多样性程度不高。本研究还发现IEL002自身并不能氧化单质硫,但它能促进Acidithiobacillus thiooxidans IEL001对单质硫的氧化。     

粉状活性焦在双层滤料颗粒床中的脱硫试验研究

在双层滤料颗粒床模型试验台上对粒径为300～400目的粉状活性焦进行了脱硫试验,研究了温度、O2和水蒸气体积分数、气体流速、再生次数对脱硫效果的影响.试验结果表明.温度为120℃、O2体积分数为8%、水蒸气体积分数为10%条件下,脱硫效果最好;粉状活性焦在双层滤料颗粒床中经过7次重复吸附.达到硫饱和吸附量为66.2 mg/g.粉状活性焦再生试验表明,随着再生次数的增加.粉状活性焦的脱硫性能呈下降趋势.     

多孔硅酸钙滤料吸附床除磷试验研究

以多孔硅酸钙滤料为吸附载体处理含磷的二沉池出水.通过静态吸附试验和动态吸附试验,研究了滤料粒径及投加量、初始pH、反应时间、温度以及滤料填充高度对除磷效果的影响.在静态吸附试验中,取初始磷质量浓度为4.98 mg/L的含磷废水100 mL,当多孔硅酸钙滤料粒径为4～14目,投加量为1.0g,吸附时间为2.5h,温度为25℃,溶液初始pH为7.0～9.0时,磷的去除率可达95％以上,出水磷满足《城镇污水处理厂污染物排放标准》(GB 18918-2002)的一级A标准(≤0.5 mg/L).动态吸附试验表明,在长期运行条件下,多孔硅酸钙滤料吸附床能持续有效地去除污水中的磷,综合考虑吸附率和运行费用,选择水力停留时间为30 min,滤料填充高度为60 cm为宜.     

基于遗传算法进行EMI滤波器电感的设计

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AUSB中置曝气对CANON颗粒污泥工艺的影响

常温(25±1)℃下,向中置(R1)、底部曝气(R2)的AUSB反应器中接种絮状厌氧氨氧化(ANAMMOX)污泥,研究AUSB不同曝气位置对连续流CANON颗粒污泥工艺启动及运行的影响.结果表明,R1、R2分别于第43 d、56 d成功启动CANON颗粒污泥,平均粒径分别为214.79μm、205.27μm,特征值(ΔNO-3-N/ΔTN)为0.128、0.129.低氨氮(90 mg·L-1)下,逐步增大氮负荷(NLR),AUSB中置曝气更利于CANON颗粒粒径的持续增长及脱氮负荷(NRR)的提高,R1于第88 d颗粒平均粒径即增至507.46μm,NRR达0.277 kg·(m3·d)-1;R2污泥颗粒历时108 d,粒径增长至467.72μm,NRR仅为R1的87.73%.底部曝气AUSB全程好氧模式下长期运行,亚硝酸盐氧化菌(NOB)显著增殖,第125 d后特征值增至0.136±0.004,NRR仅(0.231±0.015)kg·(m3·d)-1;而中置曝气AUSB特定的缺氧/好氧模式有效抑制了NOB活性,特征值维持在0.127±0.003,NRR为(0.262±0.019)kg·(m3·d)-1.AUSB中置曝气可促进絮状ANAMMOX污泥演变至CANON颗粒污泥,且系统脱氮性能及运行稳定性均优于底部曝气AUSB.     

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ABR反应器的设计

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