结合外场观测分析珠三角二次有机气溶胶的数值模拟

结合2008年11月18~25日期间珠三角地区的二次有机气溶胶(SOA)外场观测数据,验证区域空气质量模式WRF/Chem(weather research and forecasting model with chemistry)中两种SOA化学机制——VBS(volatile basis set)和SORGAM(secondary organic aerosol model)对珠三角SOA的模拟效果.VBS机制考虑了更为广泛的SOA前体物和化学老化过程,SOA模拟值更接近观测值,能合理反映SOA观测值的逐天变化趋势,与观测值的平均绝对偏差和相关性分别是-4.88μg·m-3和0.91,而SORGAM机制的分别为-5.32μg·m-3和0.18.利用VBS机制模拟区域内SOA的时空分布,结果显示SOA浓度具有显著的昼夜变化特征,浓度峰值出现在中午时段.受到输送和臭氧区域分布的影响,各城市SOA浓度差异显著,下风向的城市(如中山、珠海、江门)SOA浓度较高.     

中国地区二次有机气溶胶的时空分布特征和来源分析

二次有机气溶胶(SOA)由于其在大气污染、气候变化与人体健康方面的影响,是我国大气环境中一种重要的污染物.确定中国SOA分布规律以及产生来源是大气污染防治的前提.利用全球化学传输模型(Model for Ozone and Related Chemical Tracers,Version 4,MOZART4)并集成多相SOA参数化方案,模拟了中国地区SOA的时空分布,并按前体物分区域进行了来源分析.结果表明,受SOA前体物排放分布的影响,中国地区的SOA主要分布在东部和南部地区,并且夏季SOA产量是冬季产量的2.5倍.中国地区分布的SOA由人为源排放产生占55%,高于自然源(45%);并且境内排放贡献了我国SOA产量的77%,主要影响东部近地面大气的浓度分布.境外排放主要影响我国西部地区,尤其是对高空SOA分布影响显著.     

Second organic aerosol formation from the ozonolysis of -pinene in the presence of dry submicron ammonium sulfate aerosol

An indoor chamber facility is described for investigation of atmospheric aerosol chemistry. Two sets of α-pinene ozonolysisexperiments were conducted in the presence of dry ammonium sulfate seed particle: ozone limited experiments and α-pinene limitedexperiments. The concentration of gas phase and particle phase species was monitored continuously by on-line instruments andrecorded automatically by data sampling system. The evolution of size distribution was measured by a scanning mobility particlesizer (SMPS), and α-pinene consumed was measured using GC-FID. Secondary organic aerosol (SOA) produced for seed-free systemis 100% organic in content, resulting from a sufficient supersaturation of low volatility organics to produce homogeneous nucleationfollowed by condensation to the aerosol. Secondary organic aerosol produced in seeded system is a mixture of organic and inorganicconstituents, initially forms via condensation onto the inorganic particles, and subsequent growth occurs via absorption into the organicsurface coating the inorganic core. Although the formation process and the size distribution for seed-free system and seeded system isdifferent, the ultimate mass of SOA formed is equal, and SOA yield for the two system located in the same regression line when usingone-product model, suggesting that the presence of dry ammonium sulfate seed has no measurable effect on the total aerosol yield, and the dry seed particle acts solely as a site upon which organic deposition occurs.     

北京市二次有机气溶胶生成潜势的日变化规律

二次有机气溶胶(secondary organic aerosol,SOA)是大气细粒子(PM_(2.5))的重要组成部分.研究实际大气SOA生成潜势的日变化规律对于认知SOA生成转化机制及其对大气细粒子污染的影响具有重要意义.首次使用氧化流动管反应器(oxidation flow reactor,OFR)研究了北京夏季城市大气SOA生成潜势的日变化规律,利用高浓度的羟基自由基(·OH)氧化进入反应器内的环境空气,直接测定SOA的生成潜势.结果表明,一天内,SOA生成潜势的小时均值在3.9~9.4μg·m~(-3)范围内变化,呈现夜间高白天低的趋势,在16:00左右达到最低.SOA生成潜势和甲苯等城市典型挥发性有机物(volatile organic compounds,VOCs)变化趋势一致,而和臭氧浓度反相关.实验结果表明,除了边界层高度变化影响污染物浓度进而影响SOA生成潜势以外,夏季白天强烈的光化学反应导致环境大气VOCs的消耗,对降低环境气体白天的SOA生成潜势值也有重要影响.同国外同类研究相比,北京环境大气由于具有更高的VOCs浓度,其SOA生成潜势要明显高于其他地区,可能对北京地区细颗粒物污染具有重要贡献.     

天津隧道机动车VOCs污染特征与排放因子

应用隧道测试方法在天津市五经路隧道于工作日和非工作日对机动车挥发性有机物(VOCs)污染特征及排放因子(EFs)进行研究,采用3.2 L真空采样罐采集隧道内气体样品,应用气相色谱-质谱联用仪(GC-MS)对罐内VOCs组分进行分析,得到99种组分的定量结果.对VOCs浓度水平与变化特征、EFs进行了分析,计算隧道内VOCs的臭氧生成潜势(OFPs)和二次有机气溶胶生成潜势(SOAFPs),并与已发表的研究数据进行了对比.结果表明,隧道入口VOCs平均浓度为(190.85±51.15)μg·m~(-3),中点平均浓度为(257.44±62.02)μg·m~(-3).隧道总排放因子为(45.12±10.97) mg·(km·辆)-1,烷烃、烯烃、炔烃、芳香烃、卤代烃和含氧VOCs(OVOCs)的EFs分别为(22.79±7.15)、(5.04±1.20)、(0.78±0.34)、(9.86±2.81)、(0.26±0.17)和(6.25±2.27) mg·(km·辆)-1,与2009年测试结果相比下降明显.其中,异戊烷、甲苯、乙烯、甲基叔丁基醚(MTBE)和乙烷是机动车排放VOCs中排放因子较高的组分;甲基叔丁基醚/苯(MTBE/B)、甲基叔丁基醚/甲苯(MTBE/T)比值分别为1.07和0.77,说明蒸发排放对机动车排放VOCs的贡献不可忽视.隧道内VOCs的OFPs和SOAFPs分别为(145.50±37.85) mg·(km·辆)-1和(43.87±12.75) mg·(km·辆)-1,较2009年天津测试结果分别降低94.23%和90.88%,OFPs和SOAFPs的锐减与排放标准加严和油品升级密切相关.     

Large outdoor chamber experiments and computer simulations: (I) Secondary organic aerosol formation from the oxidation of a mixture of d-limonene and α-pinene

This work merges kinetic models for α-pinene and d-limonene which were individually developed to predict secondary organic aerosol (SOA) formation from these compounds. Three major changes in the d-limonene and α-pinene combined mechanism were made. First, radical–radical reactions were integrated so that radicals formed from both individual mechanisms all reacted with each other. Second, all SOA model species from both compounds were used to calculate semi-volatile partitioning for new semi-volatiles formed in the gas phase. Third particle phase reactions for particle phase α-pinene and d-limonene aldehydes, carboxylic acids, etc. were integrated. Experiments with mixtures of α-pinene and d-limonene, nitric oxide (NO), nitrogen dioxide (NO₂), and diurnal natural sunlight were carried out in a dual 270 m³ outdoor Teflon film chamber located in Pittsboro, NC. The model closely simulated the behavior and timing for α-pinene, d-limonene, NO, NO₂, O₃ and SOA. Model sensitivities were tested with respect to effects of d-limonene/α-pinene ratios, initial hydrocarbon to NO_x (HC₀/NO_x) ratios, temperature, and light intensity. The results showed that SOA yield (Y_SOA) was very sensitive to initial d-limonene/α-pinene ratio and temperature. The model was also used to simulate remote atmospheric SOA conditions that hypothetically could result from diurnal emissions of α-pinene, d-limonene and NO_x. We observed that the volatility of the simulated SOA material on the aging aerosol decreased with time, and this was consistent with chamber observations. Of additional importance was that our simulation did not show a loss of SOA during the daytime and this was consistent with observed measurements.     

成都秋季大气污染过程VOCs特征及SOA生成潜势

利用在线气相色谱-质谱（GC-FID/MS）监测系统,对成都市城区秋季典型大气污染期间环境空气中的77种挥发性有机物（VOCs）进行连续监测,分析了污染前期、污染中期、污染后期VOCs的污染特征、日变化规律.结果表明,成都市城区典型污染前期VOCs体积分数为38.9×10^-9;污染中期VOCs体积分数迅速增加,比污染前期高3.7倍,达到143.4×10^-9,污染后期VOCs体积分数为35.7×10^-9.污染前期VOCs日变化不明显,污染中期、后期VOCs日变化呈双峰性,分别出现在每天车流量高峰时段.此外,利用气溶胶生成系数（FAC）评估了不同污染阶段VOCs对二次有机气溶胶（SOA）的生成潜势,污染前期、污染中期、污染后期SOA浓度值分别为1.1,3.1,1.5 μg/m³,芳香烃是SOA的主要前体物.     

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.     

南京北郊VOCs对臭氧和二次有机气溶胶潜在贡献的研究

2013年3月1日~2014年2月28日采用GC5000在线气相色谱仪对南京北郊大气环境中的挥发性有机物(VOCs)进行了为期一年的连续监测,分析了VOCs的组成特征及季节、日变化规律,并结合PMF受体模型,采用最大增量反应活性(MIR)系数及气溶胶生成系数(FAC)分析了VOCs及其各来源的O3和SOA生成潜势.结果显示,南京北郊大气环境中TVOCs小时平均体积分数为45.63×10-9,TVOCs及各组分浓度呈现秋冬季高、夏季低的季节变化特征和双峰结构的日变化规律.SOA总生成量约为2.07μg/m3,芳香烃对其贡献率最大,占95.93%,其中的苯系物是生成SOA的优势物种;烯烃对OFP的贡献最大,接近65%;烷烃虽为VOCs的优势组分,却并非OFP和SOA的主要贡献者.不同季节VOCs的受体模型解析结果显示,工业排放和汽车尾气是南京北郊最主要的VOCs来源.富含苯系物的VOCs来源对SOA的贡献最大,对OFP贡献最大的则为富含乙、丙烯及异戊二烯的VOCs来源;春、秋、冬三季汽车尾气及工业排放(包括石化工业)二源对大气中的VOCs浓度、SOA的贡献及OFP的贡献影响最为显著,而夏季溶剂使用及植物源对SOA及OFP的贡献不容忽视.     

中原城市群国家干线公路SOA生成潜势估算

二次有机气溶胶(SOA)是大气污染的主要成分之一,估算汽车尾气所生成的SOA对交通大气污染治理具有重要意义.本文基于国家干线公路交通量调查数据,根据监测站点和代表路段长度建立了中原城市群干线路网线性参考系统,并以车流量为基础数据,采用排放系数法测算出中原城市群干线道路VOCs排放量,再根据气溶胶生成系数对SOA的生成潜...