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     

岗南水库沉积物间隙水有色溶解有机物的时空分布特征及差异分析

有色可溶性有机物(CDOM)作为溶解性有机物的重要组分,影响着水体中污染物质的形态特征和迁移转化过程.本研究运用紫外-可见光谱技术(UV-vis)以及三维荧光光谱(EEMs)技术结合平行因子分析法(PARAFAC),对岗南水库自入库河口到坝前主库区四季演变过程中沉积物间隙水CDOM的分布、光谱特征以及来源进行解析.结果表明,岗南水库沉积物间隙水CDOM的相对浓度a_(254)、a_(260)、a_(280)和a_(355)存在显著的季节差异,并且相对浓度大小为夏季春季秋季冬季;沉积物间隙水CDOM的E2/E3、E3/E4、E4/E6以及S_R存在显著的季节差异,呈现冬季高夏季低的特征;秋冬季的E2/E3以及E3/E4明显高于春夏季,并且秋冬季的E3/E4大部分均大于3.5,表明秋冬季沉积物间隙水CDOM具有更小的分子量和更低的腐殖化程度;三维荧光光谱通过PARAFAC解析出3种组分,分别为类酪氨酸(C1)、短波类富里酸(C2)和降解的腐殖类物质(C3),并且3种荧光组分间具有显著的正相关性(P0.001);岗南水库沉积物间隙水的CDOM总荧光强度和各荧光组分荧光强度呈现显著的季节差异,总荧光强度以及各组分的荧光强度呈现春季的最高、秋冬季次之、夏季最低的分布特征;秋冬季各个荧光组分占比不存在显著差异,春夏季各个荧光组分占比不存在显著差异,秋冬季与春夏季各个荧光组分占比存在显著差异;秋冬季沉积物间隙水CDOM生物源指数(BIX)和荧光指数(FI)均高于春夏季,表明秋冬季CDOM的自生源强于春夏季,与腐殖程度指标(HIX)的结果相吻合;PCA结合Adonis分析显示沉积物间隙水CDOM的光谱特征呈现显著的季节差异(P0.001);并且组分C1、C2、C3以及水质参数[氨氮、硝氮、亚硝氮、溶解性总氮以及溶解性总磷]均有很好的线性回归方程.综上,通过对岗南水库沉积物间隙水CDOM光谱特征进行研究,可以为分析岗南水库有机物污染特征和水质管理提供技术支持.     

基于遥感尾气监测的柴油车气态污染物排放因子计算方法研究

采用遥感尾气测试系统实测了柴油车在实际道路工况下的CO、HC和NO排放特征,修正了排放因子的计算方法,并与车载排放测试系统（PEMS）实测结果进行了验证,获得了实测车辆的CO、HC和NO排放因子.测试结果显示,在各种遥感监测的工况下柴油车尾气中均含有较高浓度的氧气,未考虑氧气影响的燃烧方程反演获得的各污染物体积浓度计算值与PEMS实测值的偏差较大,且氧气浓度越大,偏差越大.经过氧气修正的燃烧方程反演计算的尾气浓度与PEMS实测值吻合度大幅提升,适用于实际工况下遥感检测车辆尾气的反演计算.修正算法得到CO、HC和NO的排放因子离散性较小,精确度较高,可以为量化柴油车尾气排放贡献提供科学依据.     

Development of a static test apparatus for evaluating the performance of three PM2.5 separators commonly used in China

PM_(2.5) separator directly affects the accuracy of PM_(2.5) sampling.The specification testing and evaluation for PM_(2.5) separator is particularly important,especially under China's wide variation of terrain and climate.In this study,first a static test apparatus based on polydisperse aerosol was established and calibrated to evaluate the performance of the PM_(2.5) separators.A uniform mixing chamber was developed to make particles mix completely.The aerosol concentration relative standard deviations of three test points at the same horizontal chamber position were less than 0.57%,and the particle size distribution obeyed logarithmic normal distribution with an R~2 of 0.996.The flow rate deviation between the measurement and the set point flow rate agreed to within ± 1.0% in the range of -40 to 50℃.Secondly,the separation,flow and loading characteristics of three cyclone separators(VSCC-A,SCC-A and SCC112) were evaluated using this system.The results showed that the 50% cutoff sizes(D_(50)) of the three cyclones were 2.48,2.47 and 2.44 μm when worked at the manufacturer's recommended flow rates,respectively.The geometric standard deviation(GSD) of the capture efficiency of VSCCA was 1.23,showed a slightly sharper than SCC-A(GSD = 1.27),while the SCC112 did not meet the relevant indicator(GSD = 1.2 ± 0.1) with a GSD = 1.44.The flow rate and loading test had a great effect on D_(50),while the GSD remained almost the same as before.In addition,the maintenance frequency under different air pollution conditions of the cyclones was summarized according to the loading test.     

基于野外原位抽注试验和同位素技术的含水层反硝化速率研究

反硝化作用是地下水硝酸盐污染去除最重要的过程.由于水文地质条件和水文地球化学环境的复杂性和不确定性,精准测定含水层反硝化速率是反硝化过程的研究难点.选取潮白河冲洪积扇中部中国环境科学研究院地下水创新野外基地作为研究区,基于野外原位试验和15N同位素示踪法提出一种含水层反硝化速率的测定方法.该方法综合体现了研究区实际水文地质条件和水文地球化学环境对反硝化作用的影响,并充分考虑了硝酸盐在含水层中稀释弥散作用对计算结果的影响.结果表明:①潮白河冲洪积扇中部某地地下26~28 m处于还原环境,含水介质以粉细砂为主,ρ（NO₃-N）平均值为2.77 mg/L.②地下26~28 m反硝化速率在349.52~562.99 μg/（kg·d）（以N计,下同）之间,平均值为450.31 μg/（kg·d）.通过与研究区含水介质、采样深度和硝酸盐背景值相似的国内外案例对比研究,初步评估结果处于合理区间.③测试结果具有一定不确定性,主要来自忽略中间产物NO₂-和NO的计算方法、扰动采样方法、N₂O的操作规范程度及采样频率等方面.研究方法为测定含水层硝酸盐速率研究提供了新的思路,研究结果可为地下水中硝酸盐转化过程机理研究、地下水硝酸盐污染修复及风险管控提供关键的理论支撑数据.      

弹射起飞和拦阻着陆冲击试验方法探讨

目的研究舰载机机载装备弹射起飞和拦阻着陆冲击试验的工程实现方法。方法从GJB 150.18A—2009、MIL-STD-810F/G及其提供的实测数据出发,分析弹射起飞和拦阻着陆冲击载荷特征,对几种常用试验方法的工程实现进行探讨和比较。结果弹射起飞和拦阻着陆冲击具有瞬态、交变、低频、大位移、高速度等特征。阻尼正弦波方法的实施路径比较明确,复杂波形再现方法实施路径比较模糊且复杂,超长脉冲半正弦波方法具有多种局限性,前两种方法的速度、位移都较大。结论阻尼正弦波方法较复杂波形再现方法更容易实现,但两者都需要大位移、高速度的专用冲击试验设备和适当的波形处理技术,超长脉冲半正弦波方法在前面两种标准推荐方法能够实现时,不建议使用。     

重金属离子对肺表面活性物质单层膜的影响

为了探究重金属对肺表面活性物质（PS）膜的影响,利用Langmuir–Wilhelmy膜天平,研究了不同种类和浓度的重金属离子与PS单层膜的相互作用.发现Cr³⁺、Cu²⁺、Hg²⁺、Pb²⁺、Cd²⁺、Ni²⁺6种重金属离子均使PS单层的π-A等温线G-LE相变阶段外扩,而Fe³⁺可诱导单层缩合.随后,选取Cd²⁺,Cu²⁺,Hg²⁺,Fe³⁺4种离子进一步探究了重金属浓度对PS单层膜表面活性的影响规律,进行了可压缩模量分析,并结合红外光谱（FTIR）和原子力显微镜（AFM）探究其作用机理,发现Cu²⁺,Fe³⁺和Hg²⁺均会以浓度依赖的方式与PS单层的极性头部发生络合作用,形成复合物,改变膜的稳定性;而Cd²⁺的影响明显弱于其他3种金属离子,但也能使得PS单层有序性增强.     

机载产品盐雾试验结果评定判据分析与探讨

针对当前机载产品盐雾试验标准中缺少明确、可量化评估指标,试验结果评定判据粗略笼统且以定性评价为主,已不能满足产品发展和使用环境扩展需求等现状,在总结国内外现行盐雾试验标准的结果评定要求基础上,分析当前机载产品盐雾结果评定判据存在的问题与不足,从管理和技术两个层面提出改进试验结果评定可操作性的建议,指导机载产品盐雾试验实施与评价。     

非饱和带强化反应层脱氮的试验研究

自然堆肥过程中,畜禽养殖产生的粪污渗滤液入渗土壤非饱和带.高浓度有机氮在微生物作用下经由复杂的地球化学过程转化为各种含氮物质,其中硝酸盐迁移能力较强,在降雨条件下入渗地下水,造成区域性地下水硝酸盐污染.在非饱和带中构建由木屑和壤土组成的强化反应层,通过间歇性的原位淋溶脱氮试验,系统地研究了非饱和带含水量及COD、硝态氮、亚硝态氮和氨氮的浓度变化规律,评价了强化反应层的脱氮能力.研究结果表明:①反应层中木屑材料的强吸水特性使得灌水后短时间内反应层含水量大幅提升,形成有利于反硝化进行的厌氧环境.木屑通过水解作用释放大量溶解性有机碳,供给反硝化微生物进行脱氮.②在入渗硝态氮浓度为170.00 mg·L~(-1)条件下,反应层对硝态氮去除率最高可达97.63%.反应层脱氮量随处理水量增加而提升,当上层为砂土时脱氮量最高,可达24.61 g·m~(-3).③反应层中的NO~-_3-N发生了完全反硝化,出水中NO~-_2-N浓度低于0.5 mg·L~(-1),几乎不发生积累.同时,反应层中发生的DNRA过程使氨氮浓度小幅升高.强化脱氮反应层可阻控硝酸盐污染地下水.