2018年春节期间京津冀地区污染过程分析

为了解2018年春节期间京津冀地区空气污染情况,利用近地面污染物浓度数据、激光雷达组网观测数据,结合WRF气象要素、颗粒物输送通量和HYSPLIT气团轨迹综合分析污染过程.结果表明,春节期间出现3次污染过程.春节前一次污染过程,各站点PM_2.5浓度均未超过200μg/m³;除夕夜,廊坊站点PM_2.5峰值浓度达到504μg/m³,是清洁天气的26倍;年初二~初五,各站点PM_2.5始终高于120μg/m³,且污染主要聚集在500m高度以下,北京地区存在高空传输,800m处最大输送通量达939μg/（m³·s）,此次重污染过程为一次典型的区域累积和传输过程.京津冀地区处于严格管控状态时,燃放烟花爆竹期间PM_2.5峰值浓度可达无燃放时PM_2.5峰值的3.2倍.为防止春节期间重污染现象的发生,需对静稳天气下燃放烟花炮竹采取预防对策.     

Regulated emission characteristics of in-use LNG and diesel semi-trailer towing vehicles under real driving conditions using PEMS

On-road driving emissions of six liquefied natural gas(LNG) and diesel semi-trailer towing vehicles(STTVs) which met China Emission Standard IV and V were tested using Portable Emission Measurement System(PEMS) in northern China.Emission characteristics of these vehicles under real driving conditions were analyzed and proved that on-road emissions of heavy-duty vehicles(HDVs) were underestimated in the past.There were large differences among LNG and diesel vehicles, which also existed between China V vehicles and China IV vehicles.Emission factors showed the highest level under real driving conditions, which probably be caused by frequent acceleration, deceleration, and start-stop.NOx emission factors ranged from 2.855 to 20.939 g/km based on distance-traveled and 6.719–90.557 g/kg based on fuel consumption during whole tests, which were much higher than previous researches on chassis dynamometer.It was inferred from tests that the fuel consumption rate of the test vehicles had a strong correlation with NOx emission, and the exhaust temperature also affected the efficiency of Selected Catalytic Reduction(SCR) aftertreatment system, thus changing the NOx emission greatly.THC emission factors of LNG vehicles were 2.012–10.636 g/km, which were much higher than that of diesel vehicles(0.029–0.185 g/km).Unburned CH_4 may be an important reason for this phenomenon.Further on-road emission tests, especially CH_4 emission test should be carried out in subsequent research.In addition, the Particulate Number(PN) emission factors of diesel vehicles were at a very high level during whole tests, and Diesel Particulate Filter(DPF)should be installed to reduce PN emission.     

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.     

Synergistic effects of Cu species and acidity of Cu-ZSM-5 on catalytic performance for selective catalytic oxidation of n-butylamine

In this work, a series of Cu-ZSM-5 catalysts with different SiO₂/Al₂O₃ ratios (25, 50, 100 and 200) were synthesized and investigated in n-butylamine catalytic degradation. The n-butylamine can be completely catalytic degradation at 350°C over all Cu-ZSM-5 catalysts. Moreover, Cu-ZSM-5 (25) exhibited the highest selectivity to N₂, exceeding 90% at 350°C. These samples were investigated in detail by several characterizations to illuminate the dependence of the catalytic performance on redox properties, Cu species, and acidity. The characterization results proved that the redox properties and chemisorption oxygen primarily affect n-butylamine conversion. N₂ selectivity was impacted by the Brønsted acidity and the isolated Cu²⁺ species. Meanwhile, the surface acid sites over Cu-ZSM-5 catalysts could influence the formation of Cu species. Furthermore, in situ diffuse reflectance infrared Fourier transform spectra was adopted to explore the reaction mechanism. The Cu-ZSM-5 catalysts are the most prospective catalysts for nitrogen-containing volatile organic compounds removal, and the results in this study could provide new insights into catalysts design for VOC catalytic oxidation.     

加入SOA示踪的深圳大气PM2.5受体模型源解析

为厘清包括二次有机气溶胶（SOA）在内的深圳市区PM_2.5各种一次和二次来源贡献,本文于2017年9月2日~2018年8月29日在深圳市大学城点位开展PM_2.5样品采集,并进行化学组分和水溶性有机物（WSOM）质谱测量,共获得162组有效数据.观测期间深圳市大气PM_2.5平均质量浓度为26μg/m³,在传统PMF源解析的基础上加入羧基离子碎片（CO₂⁺）作为SOA的示踪物,加入水溶性有机氧（WSOO）用于计算各因子O/C,验证有机物解析效果.结果表明,SOA可以被独立解析出,其O/C明显高于其他一次污染源中有机物;机动车、二次硫酸盐、二次硝酸盐、SOA为最主要的4个源,对PM_2.5质量浓度的贡献分别为25%、23%、17%和10%,船舶、地面扬尘、老化海盐、建筑尘、生物质燃烧、燃煤和工业贡献均在5%以内.各个源的变化特征表明,机动车、二次硫酸盐、二次硝酸盐、SOA等源贡献呈现冬高夏低的季节特征,与冬季季风条件下源自内陆的污染传输密切相关.污染天气时,二次硝酸盐和SOA的贡献增加相对最显著,因此NOx和挥发性有机物是减排的关键.     

Concentrations and chemical compositions of PM10 during hazy and non-hazy days in Beijing

In order to study the concentrations of major components,characteristics and comparison in hazy and non-hazy days of PM_(10) in Beijing,aerosol samples were collected at urban site in Beijing from December 29,2014 to January 22,2015.Heavy metals like Zn,Pb,Mn,Cu,As,V,Cr and Cd were deeply studied considering their toxic effects on human being;nine water-soluble inorganic ions(SO_4~(2-),NO_3~-,NH_4~+,Na~+,K~+,Cl~-,Ca~(2+) and Mg~(2+)) and carbon fractions(OC and EC) were also analyzed.The concentrations of heavy metals were 1.03–1.98 times higher in hazy days than those in non-hazy days,mainly due to biomass burning and coal burning.The trends in total heavy metals concentrations were basically consistent with the trends in PM concentrations except for two obvious periods(12.29–12.30;1.14–1.15);but when air masses accumulated locally or around Beijing,trends in PM concentrations and heavy metals were opposite.The proportion for NO_3~-/SO_4~(2-) indicated that mobile sources such as automobiles were important reasons for haze in Beijing.Correlation between OC and EC during non-hazy days was strong(R~2= 0.95) but it was low(R~2= 0.67) during hazy days,and large variations for OC/EC values occurred in hazy days.The calculated mass concentration of SOC is 2.58 μg/m~3,which only accounted for 10.1% of the OC concentration.When air masses from the far north-west,they decreased PM concentration in Beijing and they were relatively clean;however,those from the near east,south-east and south of the mainland increased PM concentration and they were dirty.     

大兴安岭5种乔木树种燃烧释放PM2.5中水溶性元素特性

采用自主设计的生物质燃烧实验装置,在不同燃烧状态（明燃、阴燃）下,对大兴安岭林区5种典型乔木树种的不同部位（枝、叶、皮）燃烧释放PM_2.5中的水溶性元素特性进行研究.结果显示,不同树种间PM_2.5的排放因子差异显著,排放范围为（2.408±0.854）~（9.227±1.172）g/kg.5种乔木树种燃烧释放PM_2.5中主要检测到Mg、Ca、K等16 种元素,其中Ca、K、Zn、Mg 4种元素的排放因子明显大于其它元素.不同树种间元素排放因子差异较大,针叶树的排放因子一般高于阔叶树.除Cd元素外,不同器官间排放的元素总量无明显差异.不同树种不同器官燃烧释放PM_2.5中水溶性元素的占比顺序较为一致,其中Ca、K、Zn和Mg 4种元素的排放因子在枝、叶、皮中均较高.此外,燃烧状态对元素排放特征影响较大,Li、Mg、Ca等7种元素的排放因子均表现为明燃显著高于阴燃.     

典型西南工业城市春冬季PM2.5来源与潜在源区分析——以柳州市为例

为了揭示柳州城区春冬季PM_2.5的来源及其潜在源区分布和贡献,利用2018年24h自动监测数据和气象数据对柳州市大气污染物浓度变化特征进行了分析,并且使用后向轨迹模型（HYSPLIT）对春冬季柳州市PM_2.5逐日72h气流后向轨迹和前向轨迹进行聚类分析,同时结合潜在源贡献因子分析法（WPSCF）和轨迹浓度权重法（WCWT）对其潜在源区和浓度贡献进行了分析.结果显示,（1）在研究期内,不利的主导风向和工业区布局导致研究区PM_2.5在春冬季污染较严重,且工业源和交通源是其主要本地来源;（2）春冬季PM_2.5高值主要来源于西北和东南方向,其中,西北向PM_2.5主要来源于本地排放,且浓度在空间上呈现西高东低的趋势;（3）春季后向轨迹PM_2.5浓度整体大于冬季,春冬季中对柳州市PM_2.5影响最大轨迹均来自东部的短距离输送,而来自西北的气流轨迹输对PM_2.5贡献最低.春冬季柳州市大气PM_2.5通过气流传输对贵州地区大气环境有较大影响;（4）春季,柳州市PM_2.5的主要潜在源区分布在广西东南部、广东中西部、南海沿岸海域、湖南中部、江西西北部、湖北东部及安徽西北部;冬季,主要分布在广西东南部、广东西南部和南海沿岸海域.     

2018年秋冬季长江三角洲区域PM2.5污染来源数值研究

使用WRF-Chem和WRF-FLEXPART模式定量研究了2018年秋冬季,尤其是在明显冷空气影响时的长江三角洲PM_2.5来源贡献.结果表明：2018年秋冬季长江三角洲以外的跨区域输送对长江三角洲PM_2.5的贡献占15.9%,长江三角洲内部排放贡献占84.1%,长江三角洲区域内部排放及污染相互传输的影响比长江三角洲外跨区域输送的影响更为显著.而在冷空气影响时段中,跨区域输送对长江三角洲PM_2.5的贡献率为33.1%,约为整个秋冬季长江三角洲外部跨区域平均输送贡献率的2倍,输送影响更为明显;输送对长江三角洲三省一市的贡献为46.2%~56.2%,其中跨区域输送的贡献10.2%~38.6%,也明显大于各自秋冬季的平均水平.在冷空气影响时段,长江三角洲四座重点城市（上海、合肥、南京、杭州）的污染潜在输送路径主要以中东路为主;上海、南京受到长江三角洲以外的污染潜在贡献较多,超过30%;杭州受到长江三角洲以外的污染潜在贡献较少,为16.1%.     

降水和风对大气PM2.5、PM10的清除作用分析

对合肥2015—2017年的降水、风和PM_(2.5)、PM_(10)浓度观测数据统计研究发现,降水对PM_(2.5)、PM_(10)有一定的清除作用,尤其在秋冬季节.秋冬季节小雨、中雨分别导致PM_(2.5)和PM_(10)浓度降低23.1%、40.4%和32.0%、63.7%.雨日PM_(2.5)/PM_(10)比例上升8.4%,表明降水对PM_(10)清除作用更显著.降水前后PM_(2.5)浓度变化与降水前PM_(2.5)浓度、降水强度、降水时长密切相关.当降水强度大于4 mm·h~(-1)或PM_(2.5)初始浓度高于115μg·m~(-3)时,降水对PM_(2.5)产生明显清除作用;而降水强度小于1 mm·h~(-1)或PM_(2.5)初始浓度低于115μg·m~(-3)时由于吸湿增长作用极易造成PM_(2.5)浓度反弹升高;且持续3 h以上雨强介于1～4 mm·h~(-1)的降水也对PM_(2.5)产生清除作用.降水前后PM_(10)浓度变化与初始浓度密切相关,而与雨强相关性较弱.当PM_(10)初始浓度大于50μg·m~(-3),降水就对PM_(10)产生明显清除作用,且PM_(10)初始浓度越高,降水后PM_(10)浓度下降越多.风速大于2 m·s~(-1)可显著降低PM_(2.5)浓度,因此,当风速大于4 m·s~(-1)时合肥较少出现中度及以上污染,但易造成地面起尘,使PM_(10)浓度不降反升.合肥冬季严重污染主要出现在西北风向,夏季中度以上污染天气较少,主要出现在风速低于3 m·s~(-1)的东南风向.