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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.
测定环境空气中微量氟的方法一般采用滤膜法,但此法工作量大,针对这种情况,本文作两点改进:一是将采集的两张滤膜同时测定;二是将测定过程中的搅拌时间缩短,这样不影响测定结果的准确性,而且降低了工作量。 相似文献
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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. 相似文献
5.
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。 相似文献
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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. 相似文献
8.
目的 探究碳纤维复合材料在舰船应用时与金属材料的电偶腐蚀问题。方法 针对一种典型舰船用碳纤维增强乙烯基树脂复合材料,在青岛海洋大气环境下开展0.5、1、1.5、2 a期的自然曝晒试验,进而采用电化学分析手段考察其与低合金钢的电偶腐蚀效应,结合老化机制探究碳纤维复合材料的老化行为对其与钢电偶腐蚀的影响。结果及结论 在青岛大气环境曝晒不同周期的复合材料试样,开路电位与低合金钢相差较大,存在较高的电偶腐蚀倾向。随曝晒时间的延长,复合材料表面微裂纹不断产生、扩展,导致电化学反应活性点增多,两者电偶电流密度随之增大。在青岛海洋大气环境下暴露2 a后,碳纤维增强乙烯基树脂复合材料与低合金钢的电偶电流为0.356 9 μA/cm2,两者的电偶腐蚀敏感性达到B级。 相似文献
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10.