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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.
提出了滤纸法测定悬浮物时,水样的酸碱度,取样量的多少对悬浮物测定有直接的影响。通过实验验证,对于偏酸,偏碱的水样用酸碱中和后再过滤即可消除影响,取样量应根据悬浮物的不同而定。 相似文献
3.
恶臭污染防治技术及工程实践 总被引:10,自引:0,他引:10
白韬光 《辽宁城乡环境科技》2002,22(5):36-40
目前,恶臭污染对人类生活的危害日益加剧,文中介绍了几种恶臭污染物的防治技术。对生物滴滤池 活性炭吸附工艺进行了探讨,工程实例表明具有良好的治理效果。 相似文献
4.
大阻力配水系统滤池由于采用穿孔钢管配水 ,而穿孔钢管容易腐蚀、结垢 ,导致孔眼堵塞 ,再若高位水箱反冲强度掌握不当 ,会使承托层和滤料冲洗混乱 ,滤池不能正常运行。针对这一问题 ,湖州市自来水公司与浙江省玉环净化厂联手 ,利用该厂滤板、滤头及有关专利新技术 ,对自来水公司的 6万t/d快速滤池进行改造 ,运行半年来 ,取得了满意的结果。 相似文献
5.
6.
7.
生物砂滤池对有机物和氨氮的去除 总被引:3,自引:0,他引:3
当在常规工艺前加生物预处理并取消预加氯时,砂滤池就成为生物砂滤池。与普通砂滤池相比其对有机物、氨氮和浊度的去除率都有很大的提高。实验以珠江源水为水源研究了生物砂滤池对高锰酸盐指数、NH3-N、NO2--N和浊度的去除,在实验期间生物砂滤池出水高锰酸盐指数、NH3-N、浊度平均值分别为1.32mg/L、0.098mg/L、0.171NTU,其相对于沉淀池出水的高锰酸盐指数、NH3-N、浊度的平均去除率分别为18.52%、72.93%、64.45%,而砂滤池出水NO2--N几乎检测不出来。滤池进水与出水溶解氧的变化也证明了砂滤池中生物的存在,并且生长状况良好。 相似文献
8.
9.
本文介绍了一种新型的过滤技术(表面过滤技术)在袋式除尘器中的应用及其特点,该技术的采用可减少除尘器的压力损失,提高滤袋的使用寿命和除尘效率. 相似文献
10.
IntroductionCleaningthefineparticlesinhightemperature (450℃ -950℃ )andhighpressureconditioncanenhancethethermalefficiencyofcleancoaltechnologiessuchasIGCCorPFBC .Rigidceramicfiltersofavarietyofstructuresareunderdevelopmentinprogramsaroundtheworld ,whichcanfi… 相似文献