北京市气溶胶的时间变化与空间分布特征

以MODIS气溶胶遥感数据与同期AERONET监测数据为基础,应用统计分析、对比分析、时间序列分析等技术手段,研究了北京地区气溶胶的时间变化和空间分布特征.结果表明,气溶胶MODIS遥感反演数据和同期AERONET监测数据吻合较好,Pearson积矩相关系数为0 789,误差为ΔAOT550 = -0.077AOT 0.03.北京地区气溶胶550 nm光学厚度AOT和细粒比η的时间变化规律性明显:夏季以城市污染气溶胶为主,光学厚度最高,且具细粒特征;春季城市污染气溶胶和春季沙尘共存,光学厚度比较高,且粗粒占一定比例;冬季以采暖燃煤气溶胶为主,光学厚度不高,但是粗粒占较大比例;秋季大气清澈,气溶胶平均光学厚度仅为0.34.空间分布方面,主要受植被覆盖和产业结构等因素影响,位于西部北部山区的延庆、密云、怀柔和门头沟区气溶胶的光学厚度低,位于东南部平原地区的昌平、顺义、通县、大兴和房山区气溶胶光学厚度总体较高.     

Long range trans-Pacific transport and deposition of Asian dust aerosols

The deposition of Asian dust aerosols during their trails-Pacific Uansport might cause significant marine phytoplankton biomass increases.However,the knowledge of the trans-Pacific dust transport,deposition,and spatial distribution is still poor due to a lack of continuous and simultaneous observations in the Asian subcontinent,the north Pacific Ocean,and North America.The severe Asian dust storm during 6 to 9 April 2001 provided an opportunity to gain a better understanding of trans-Pacific dust transport and deposition,using a comprehensive set of observations from satellites,ground-based light detection and ranging,aircraft,and surface observation networks.The observations and model simulations outline the general pattern of dust transport,deposition,vertical profile,and spatial distribution.The following points were observed(1)the surface dust concentrations decreased exponentially with the increasing dust transport distance from 80°E to 120°W along the transport pathway;(2)the altitude of the dust concentration peak increased with increasing transport distance in the north Pacific region;and (3) the spatial distribution of dust deposition mainly depended on the trans-Pacific transport route.     

离子色谱在气溶胶无机离子测定中的应用

综述了离子色谱技术在气溶胶可溶性无机离子测定中的应用。离子色谱技术的主要优点是检测时间短、耗费样品量少和分辨率高。它克服了化学分析法的缺点,已经成为一种优秀的样品分析检测技术,气溶胶可溶性无机离子测定中采用这一技术是很有价值的。介绍了离子色谱的原理,仪器的组成与操作,并以气溶胶中无机离子的测定流程为主线,分别概述了采样与样品处理的方法和注意事项,分离柱与淋洗液的选择和影响因素,抑制器与检测器的发展和最新动态。     

气溶胶辐射效应对气象和环境影响的观测与模拟研究

选取2015年和2019年不同代表年份,结合外场观测和数值模拟,分析了天津地区不同季节不同天气(晴天、多云、霾)下,气溶胶辐射效应对整层大气透过率和地表入射太阳辐射的影响,以及这种影响在不同年份的差异.借助WRF-Chem模式模拟分析了重污染期间气溶胶辐射效应对垂直方向上气象要素廓线、边界层结构以及PM_2.5浓度的反馈机制.结果表明:霾污染可导致大气透过率明显下降,春、秋、冬不同季节,霾污染导致中午大气透过率分别下降0.09,0.11和0.09.全年平均霾污染可导致大气透过率降低约15.5%.云量的增多也可导致大气透过率明显下降,多云天气下大气透过率相比晴天减小约22.4%.霾和云对大气透过率的影响还与太阳高度角有关,当太阳高度角>60°时,霾污染导致大气透过率下降8.6%.随污染等级提高,气溶胶对太阳辐射的衰减作用也越强,天津地区空气质量分别为Ⅰ～Ⅰ级时,中午地表入射短波辐射呈稳定下降趋势,依次为484,446,439,342,328和253W/m².重污染期间,气溶胶辐射效应导致大气低层(250m以下)降温(0.8℃)增湿(3.8%...     

上海城区二次气溶胶的形成:光化学氧化与液相反应对二次气溶胶形成的影响

二次组分是大气细颗粒物中最重要的组成部分之一.本研究旨在探究上海城区大气气溶胶颗粒物中二次组分的贡献及其形成的主要影响因素.利用高分辨率飞行时间气溶胶质谱仪(HR-TOF-AMS)对上海城区春季及夏季的亚微米颗粒物(PM_1)进行实时的在线表征,发现有机物是PM_1中最主要的组成部分,占比为55%;其次是硫酸盐(24%)与硝酸盐(10%).进一步结合正交矩阵因子解析模型(PMF)对有机组分进行了来源解析.结果表明,一次有机气溶胶(POA)与二次有机气溶胶(SOA)分别占总有机物浓度的34%与66%; POA主要来自机动车源与餐饮源的贡献,且在春季和夏季对有机物的贡献趋于稳定.观测期间共观察到3个二次气溶胶显著生成的过程:其中,春季二次组分的显著增长过程以硫酸盐和老化的有机气溶胶在正午时段上升显著为主要特征,主要受光化学氧化过程的促进;夏季二次组分的显著生成过程主要是液相反应与光化学氧化共同促进的结果,如液相反应过程中,硝酸盐浓度与颗粒相水含量有较好的相关性(R~2=0. 72),而光化学氧化期间SOA浓度与大气氧化性(O_x)有较好的相关性.总体而言,二次组分是上海城市大气气溶胶颗粒物中最重要的组成部分,二次有机与无机组分在PM_1颗粒物中占比分别为35. 5%和43%,光化学氧化与液相反应对二次组分的形成有显著的促进作用.     

深圳秋季大气有机气溶胶来源与挥发性研究

使用热扩散管与长飞行时间气溶胶质谱联用系统对2020年深圳市秋季亚微米级气溶胶进行在线测量,获取和分析了气溶胶的化学组成及挥发性特征,并利用正矩阵因子分析法（PMF）对有机气溶胶进行了来源解析.结果显示：观测期间,气溶胶平均质量浓度为（28.3±11.1）μg/m³（9.5~76.8μg/m³）,其中,有机物占比最高,为57.9%,其次为硫酸盐（24.7%）.PMF对有机气溶胶解析结果得到四类源,分别为烃类有机气溶胶（HOA）、餐饮源有关的有机气溶胶（COA）、低氧化性的氧化有机气溶胶（LO-OOA）和高氧化性的氧化有机气溶胶（MO-OOA）.HOA、COA、LO-OOA和MO-OOA平均分别占到总有机物的9.1%、27.2%、31.8%和31.9%.进一步采用NO⁺/NO₂⁺比值法和PMF方法估算有机硝酸酯（ON）浓度,两种方法估算结果相关性良好,ON的平均浓度为0.17~0.25μg/m³,占总有机气溶胶质量的1.5%~9.7%,说明其对深圳大气气溶胶贡献显著.ON与各有机气溶胶因子的相关性比对发现,其与LO-OOA相关性最高（R=0.80）,说明其可能来源于新鲜的二次生成反应.挥发性研究结果得出,深圳市气溶胶主要化学组分挥发性顺序为氯盐≈无机硝酸盐 > 铵盐 > 有机物 > 有机硝酸酯 > 硫酸盐,对于有机气溶胶因子,其挥发性排序为LO-OOA > HOA > COA > MO-OOA,除了LO-OOA,其余因子挥发性与其氧化态排序一致,而LO-OOA从50~70℃组分下降最多,说明其所含组分挥发性差异最为明显.     

基于TEM-EDS对四川盆地大气单颗粒气溶胶的研究

为了解四川盆地大气中单颗粒气溶胶理化特征,分别在该区域典型城市（成都市）和背景地区（峨眉山）进行了大气单颗粒样品采集.基于带能谱的透射电子显微镜（TEM-EDS）对两地累计3923个单颗粒的化学组成、形貌特征及混合状态等进行了全面观测和分析,并对两地颗粒物差异性进行了对比分析.结果发现：两地气溶胶颗粒主要包括有机物、富硫、矿物、烟尘和飞灰/金属颗粒,除了以单独的外混形式存在外,大多数颗粒以两种及两种以上颗粒类型混合（即内混）形式存在.通过对成都市不同污染状况下单颗粒特征对比发现,"污染天"的内混颗粒占比高于"清洁天",分别为74.2%和68.6%;相比"清洁天","污染天"颗粒物粒径分布范围更广且峰值区间更大,表明污染过程中颗粒物的大气混合趋于更强.对比成都市与峨眉山分析结果得知,成都市以内混的有机物-硫颗粒为主导（占比为50.2%）,而峨眉山以外混的有机物颗粒为主导（占比为50.5%）;成都市含硫类颗粒物（如有机物-硫颗粒）贡献高于峨眉山,而峨眉山两种含碳类颗粒（如烟尘和有机物-烟尘颗粒）占比高于成都市;此外,成都市与峨眉山两地大气颗粒物粒径分布范围及峰值区间均存在一定差异,进一步体现了两地颗粒物来源和老化混合的差异.在峨眉山,与非降雨天相比,一些易溶于水的颗粒物（如含硫类颗粒）在降雨天占比明显降低,而源自当地燃烧过程、粒径较小且疏水性强的颗粒物（如烟尘和有机物-烟尘颗粒）占比相应升高.     

成都地区气溶胶散射吸湿增长因子双变量模型

基于成都市2017年10～12月逐时的“干”气溶胶散射系数和吸收系数观测数据,结合该时段同时次的能见度（V）、相对湿度（RH）以及二氧化氮（NO₂）监测资料,利用“光学综合法”计算气溶胶散射吸湿增长因子,并探究了气溶胶散射吸湿增长因子单变量f（RH）模型的适用性及其改进方案.结果表明：幂函数、二次多项式、幂指函数形式的f（RH）模型在低RH条件下（RH<85%）均能很好地模拟气溶胶散射吸湿增长因子随RH的变化特征,但在高RH条件下（RH>85%）的模拟值会出现较大的偏差.黑碳质量浓度（C_BC）是影响气溶胶散射吸湿增长因子的另一关键变量,二者之间满足非线性关系.以RH和C_BC为自变量构建了气溶胶散射吸湿增长因子双变量f（RH,C_BC）模型,模型计算值和实测值之间的决定系数R²为0.763,平均相对误差MRE为14.28%.双变量模型f（RH,C_BC）的应用显著改善了气溶胶散射消光系数的模拟效果.     

A large-scale outdoor atmospheric simulation smog chamber for studying atmospheric photochemical processes: Characterization and preliminary application

Understanding the formation mechanisms of secondary air pollution is very important for the formulation of air pollution control countermeasures in China. Thus, a large-scale outdoor atmospheric simulation smog chamber was constructed at Chinese Research Academy of Environmental Sciences (the CRAES Chamber), which was designed for simulating the atmospheric photochemical processes under the conditions close to the real atmospheric environment. The chamber consisted of a 56-m³ fluorinated ethylene propylene (FEP) Teflon film reactor, an electrically-driven stainless steel alloy shield, an auxiliary system, and multiple detection instrumentations. By performing a series of characterization experiments, we obtained basic parameters of the CRAES chamber, such as the mixing ability, the background reactivity, and the wall loss rates of gaseous compounds (propene, NO, NO₂, ozone) and aerosols (ammonium sulfate). Oxidation experiments were also performed to study the formation of ozone and secondary organic aerosol (SOA), including α-pinene ozonolysis, propene and 1,3,5-trimethylbenzene photooxidation. Temperature and seed effects on the vapor wall loss and SOA yields were obtained in this work: higher temperature and the presence of seed could reduce the vapor wall loss; SOA yield was found to depend inversely on temperature, and the presence of seed could increase SOA yield. The seed was suggested to be used in the chamber to reduce the interaction between the gas phase and chamber walls. The results above showed that the CRAES chamber was reliable and could meet the demands for investigating tropospheric chemistry.     

Primary and secondary organic aerosol in an urban/industrial site: Sources, health implications and the role of plastic enriched waste burning

PM10 samples were collected from an urban/industrial site nearby Athens, where uncontrolled burning activities occur. PAHs, monocarboxylic, dicarboxylic, hydroxycarboxylic and aromatic acids, tracers from BVOC oxidation, biomass burning tracers and bisphenol A were determined. PAH, monocarboxylic acids, biomass burning tracers and bisphenol A were increased during autumn/winter, while BSOA tracers, dicarboxylic- and hydroxycarboxylic acids during summer. Regarding aromatic acids, different sources and formation mechanisms were indicated as benzoic, phthalic and trimellitic acids were peaked during summer whereas p-toluic, isophthalic and terephthalic were more abundant during autumn/winter. The Benzo[a]pyrene-equivalent carcinogenic power, carcinogenic and mutagenic activities were calculated showing significant (p < 0.05) increases during the colder months. Palmitic, succinic and malic acids were the most abundant monocarboxylic, dicarboxylic and hydrocarboxylic acids during the entire sampling period. Isoprene oxidation was the most significant contributor to BSOA as the isoprene-SOA compounds were two times more abundant than the pinene-SOA (13.4 ± 12.3 and 6.1 ± 2.9 ng/m³, respectively). Ozone has significant impact on the formation of many studied compounds showing significant correlations with: isoprene-SOA (r = 0.77), hydrocarboxylic acids (r = 0.69), pinene-SOA (r = 0.63),dicarboxylic acids (r = 0.58), and the sum of phthalic, benzoic and trimellitic acids (r = 0.44). PCA demonstrated five factors that could explain sources including plastic enriched waste burning (30.8%), oxidation of unsaturated fatty acids (23.0%), vehicle missions and cooking (9.2%), biomass burning (7.7%) and oxidation of VOCs (5.8%). The results highlight the significant contribution of plastic waste uncontrolled burning to the overall air quality degradation.