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     

氢氟酸的污染与防治

综述氢氟酸烷基化装置，运行过程中氢氟酸的危害，污染源的分析，防治措施及取得效果．     

基于LOADEST和数字滤波的水源地基流氮素输出定量方法应用实例

地表直接径流和基流均是流域非点源氮/磷养分输出的重要水文途径.科学认识和定量模拟基流氮/磷养分输出对于准确解析水源地水体非点源污染来源至关重要.基于Load Estimator模型和数字滤波算法,建立了定量水源地基流氮素输出的方法体系.以浙江省珊溪水源地的玉泉溪流域为例,利用玉泉溪2010-01—2013-12期间逐月总氮(TN)水质监测数据和逐日流量数据,展示了该方法的计算过程.结果表明,本文建立的水源地基流氮素输出定量方法结果合理,模拟精度高,决定系数和纳什系数分别为0.83和0.80;玉泉溪流域2010—2013年TN负荷量为141.21～274.68 t·a~(-1),平均208.63 t·a~(-1),年基流TN负荷量为84.39～168.68 t·a~(-1),平均127.69 t·a~(-1);基流对玉泉溪年均TN负荷量贡献率高达60%以上,流域基流养分输出对地表水体的污染应引起足够重视.     

基于稳定氢同位素的太原市大气单环芳烃来源

采集太原市城北和城南区域环境空气和5类污染源挥发性有机物样品,测定样品中典型单环芳烃稳定氢同位素（δD）组成,基于同位素质量平衡原理计算单环芳烃从源到环境空气受体的δD初始混合值,探讨单环芳烃来源.结果表明,柴油挥发源、溶剂挥发源、汽油挥发源（97^#）、汽油挥发源（95^#）、机动车尾气（97^#）、机动车尾气（95^#）和民用燃煤源中单环芳烃δD范围依次为：（-138.7‰~-115.5‰）、（-147.0‰~-121.0‰）、（-150.8‰~-117.6‰）、（-131.8‰~-113.8‰）、（-171.2‰~-120.0‰）、（-138.9‰~-102.7‰）和（-168.3‰~-142.3‰）,民用燃煤源中单环芳烃δD显著贫重氢同位素（D）组成,机动车尾气源与汽油挥发源中苯的δD相比显著贫D,可用于探索污染物转化过程;城北和城南环境空气中δD范围为（-131.7‰~-115.1‰）和（-131.9‰~-74.9‰）,δD初始混合值为-138.4‰和-173.9‰,体现了其来源差异.     

深圳大气PM2.5中水溶性有机物的来源特征

对2017年9月~2018年8月深圳市北部大气PM_2.5中水溶性有机物（WSOM）的质量浓度、质谱及来源结构进行测量和分析.结果表明：PM_2.5的质量浓度为（32.3±18.4）μg/m³,WSOM的质量浓度为（9.4±5.7）μg/m³,占颗粒物总有机物的（77.6%±14.0%）.质谱分析显示,WSOM的氧碳比（O/C）平均值达到（0.57±0.09）,属于二次有机物的O/C值范围,且生物质燃烧排放的离子碎片C₂H₄O₂⁺的丰度显著,说明WSOM的来源中有显著的生物质燃烧排放的有机气溶胶.为了明确WSOM的来源结构,利用正矩阵因子分解法（PMF）模型进行来源解析,发现3个合理因子：高氧化态有机气溶胶（MO-OOA）,低氧化态有机气溶胶（LO-OOA）和生物质燃烧（BBOA）,贡献比例分别为51.7%,31.8%和16.5%.MO-OOA和BBOA贡献浓度均呈现秋冬高、春夏低的季节变化特征,反向轨迹分析显示其与内陆污染传输关系密切.LO-OOA的变化相对稳定,本地源的贡献较大.结合¹⁴C同位素示踪法对秋冬季WSOM样品分析,发现机动车等化石源二次有机物是WSOM的主要来源,贡献比例达到53.9%,需继续加强对化石燃料控制来降低WSOM污染.     

邢台市秋季PM2.5及水溶性离子污染特征

为研究邢台市秋季PM_2.5污染特征,于2017年10月15日~11月14日在邢台市区对PM_2.5样品进行了采集,并对其中水溶性离子（包括Cl^-、NO₃^-、SO₄^2-、NH₄⁺、Ca²⁺、Na⁺、Mg²⁺、K⁺）进行了分析.结果显示,观测期间邢台市ρ（PM_2.5）平均值为（130.0±74.9）μg/m³,其中水溶性离子质量浓度为（69.8±11.4）μg/m³,占ρ（PM_2.5）的53.3%,NO₃^-、SO₄^2-和NH₄⁺为主要离子,占水溶性离子比例达到了89.7%. 当污染加重,水溶性离子质量浓度随ρ（PM_2.5）增大而升高,且NO₃^-、NH₄⁺及SO₄^2-占比亦逐渐升高,但其他离子占比随之下降,Ca²⁺尤为明显,表明ρ（PM_2.5）升高时主要受二次无机转化影响;观测期间SOR（硫转化率）与NOR（氮转化率）的平均值分别为0.36和0.25,表明秋季SO₂与NO₂转化速率较强,二次无机污染严重,另外SOR及NOR与温度及相对湿度呈正相关,且SOR对二者更为敏感;邢台市秋季PM_2.5呈弱碱性,NH₄⁺主要以（NH₄）₂SO₄和NH₄NO₃的形式存在;ρ（NO₃^-）/ρ（SO₄^2-）平均值为2.13,表明移动源对秋季大气颗粒物的来源贡献较大;PMF分析结果表明,二次转化源、燃烧源及扬尘源为邢台市秋季PM_2.5中水溶性离子的主要来源.     

陆浑水库沉积物重金属空间分布特征及风险评价

为了解洛阳市饮用水水源地陆浑水库沉积物中重金属污染程度,采集32个点位的表层沉积物,分析6种重金属（Cd、Cr、Cu、Ni、Pb和Zn）的空间分布特征,并运用地累积指数法、潜在生态风险指数和聚类分析等方法对研究区重金属污染程度进行评价、生态风险评价及源解析.结果表明：Cd、Cu、Pb和Zn含量超过黄河流域河南段重金属土壤背景值,分别是其8.8、2.0、6.5、2.3倍,重金属存在明显富集,且主要污染集中于坝前区域.地累积指数法评价结果显示,Cd为强污染,Pb为中-强污染.潜在生态风险指数表明,陆浑水库沉积物重金属风险呈自上游至下游逐渐增强的趋势,总体处于高度生态危害,潜在生态风险指数均值达到312.94,其中Cd为主要贡献因子.富集系数法和聚类分析结果显示：Cd、Cu、Pb和Zn主要为人为源,Cr和Pb以自然源为主.总体而言,陆浑水库沉积物中重金属Cd和Pb污染相对较重,可能会对水库水环境构成威胁.     

Role of glycine on sulfuric acid-ammonia clusters formation: Transporter or participator

Glycine(Gly) is ubiquitous in the atmosphere and plays a vital role in new particle formation(NPF).However,the potential mechanism of its on sulfuric acid(SA)-ammonia(A)clusters formation under various atmospheric conditions is still ambiguous.Herein,a(Gly)_x·(SA)_y·(A)_z(z≤x+y≤3) multicomponent system was investigated by using density functional theory(DFT) combined with Atmospheric Cluster Dynamics Code(ACDC) at different temperatures and precursor concentrations.The results show that Gly,with one carboxyl(-COOH) and one amine(-NH_2) group,can interact strongly with SA and A in two directions through hydrogen bonds or proton transfer.Within the relevant range of atmospheric concentrations,Gly can enhance the formation rate of SA-A-based clusters,especially at low temperature,low [SA],and median [A].The enhancement(R) of Gly on NPF can be up to 340 at T=218.15 K,[SA]=10~4,[A]=10~9,and [Gly]=10~7 molecules/cm~3.In addition,the main growth paths of clusters show that Gly molecules participate into cluster formation in the initial stage and eventually leave the cluster by evaporation in subsequent cluster growth at low [Gly],it acts as an important "transporter" to connect the smaller and larger cluster.With the increase of [Gly],it acts as a "participator" directly participating in NPF.     

Influence of floc dynamic protection layer on alleviating ultrafiltration membrane fouling induced by humic substances

Cake layer formation is inevitable over time for ultrafiltration (UF) membrane-based drinking water treatment. Although the cake layer is always considered to cause membrane fouling, it can also act as a “dynamic protection layer”, as it further adsorbs pollutants and dramatically reduces their chance of getting to the membrane surface. Here, the UF membrane fouling performance was investigated with pre-deposited loose flocs in the presence of humic acid (HA). The results showed that the floc dynamic protection layer played an important role in removing HA. The higher the solution pH, the more negative the floc charge, resulting in lower HA removal efficiency due to the electrostatic repulsion and large pore size of the floc layer. With decreasing solution pH, a positively charged floc dynamic protection layer was formed, and more HA molecules were adsorbed. The potential reasons were ascribed to the smaller floc size, greater positive charge, and higher roughness of the floc layer. However, similar membrane fouling performance was also observed for the negative and positive floc dynamic protection layers due to their strong looseness characteristics. In addition, the molecular weight (MW) distribution of HA also played an important role in UF membrane fouling behavior. For the small MW HA molecules, the chance of forming a loose cake layer was high with a negatively charged floc dynamic protection layer, while for the large MW HA molecules it was high with a positively charged floc dynamic protection layer. As a result, slight UF membrane fouling was induced.     

Recent advances in catalytic decomposition of ozone

Ozone (O₃), as a harmful air pollutant, has been of wide concern. Safe, efficient, and economical O₃ removal methods urgently need to be developed. Catalytic decomposition is the most promising method for O₃ removal, especially at room temperature or even subzero temperatures. Great efforts have been made to develop high-efficiency catalysts for O₃ decomposition that can operate at low temperatures, high space velocity and high humidity. First, this review describes the general reaction mechanism of O₃ decomposition on noble metal and transition metal oxide catalysts. Then, progress on the O₃ decomposition performance of various catalysts in the past 30 years is summarized in detail. The main focus is the O₃ decomposition performance of manganese oxides, which are divided into supported manganese oxides and non-supported manganese oxides. Methods to improve the activity, stability, and humidity resistance of manganese oxide catalysts for O₃ decomposition are also summarized. The deactivation mechanisms of manganese oxides under dry and humid conditions are discussed. The O₃ decomposition performance of monolithic catalysts is also summarized from the perspective of industrial applications. Finally, the future development directions and prospects of O₃ catalytic decomposition technology are put forward.