中亚咸海干涸湖床粉尘潜在扩散的时空变异分析

基于1969~2018年再分析气象资料,运用拉格朗日混合单粒子轨道（HYSPLIT）模型,计算了以咸海为中心未来7d的逐日气团轨迹,采用核密度分析法,绘制了5个层次（0~0.5,0.5~1,1~1.5,1.5~2,2~5km·agl）的气团轨迹密度图,分析了咸海干涸湖床粉尘扩散的时空变异.结果显示,粉尘潜在扩散具有季节分异.春、冬季粉尘扩散范围与密度最大,沿东北方向扩散比例分别占61%、35%,最远可达亚洲东部地区,其次是秋季;夏季粉尘扩散以0.5km为界限表现明显的高度差异.随着高度的增加,粉尘潜在扩散的密度逐渐降低.受地形与天气系统的影响,春、夏粉尘扩散呈现向东北,西南方向扩散趋势,秋、冬呈现沿东北方向扩散趋势.有利的天气条件下,咸海干涸湖床粉尘可远距离输送：在近源区沉降,影响乌兹别克斯坦及周边国家,在山区沉降,则可能加速天山雪冰融化.     

Modification and testing of a gaussian dispersion model for particulate matter in the respirable size range

Modified expression for vertical and horizontal dispersion coefficients σ_y and σ_z are proposed. The determined values of σ_y and σ_z, for a specified time span, are used in a Gaussian profile to predict pollution load. This model, being easy to use, serves as a convenient method to predict dust concentration (in the respirable size range).     

郑州市冬季大气PM2.5传输路径和潜在源分析

针对郑州市2017年12月~2018年2月的冬季气象数据和大气污染物质量浓度在线监测数据,分析了气象条件对颗粒物浓度的影响.通过混合型单粒子拉格朗日综合轨迹(HYSPLIT)方法模拟了郑州市冬季48 h的气流后向轨迹,同时进行了聚类分析,并使用潜在源贡献因子(PSCF)方法和浓度权重轨迹(CWT)方法分析了郑州市冬季PM_(2.5)的潜在污染来源和不同潜在源区对郑州市大气PM_(2.5)浓度的贡献.结果表明,低风速、高湿度和较少的降水是造成颗粒物污染严重的重要气象因素;超过60%的后向轨迹来自西北方向,其次是来自京津地区的轨迹占比为25.6%,而来自南边和东边的轨迹只占7.5%和6.1%,但对应着较高的PM_(2.5)浓度;郑州市冬季PM_(2.5)的潜在源区主要是北部的京津冀传输通道城市,包括焦作、开封、新乡、鹤壁、濮阳、安阳、邯郸和邢台,此外,相邻省份包括山西省、湖北省和安徽省部分区域对郑州市大气PM_(2.5)污染水平也有着较大的影响和贡献.     

基于AIS轨迹修复的船舶排放空间表征改进方法与应用

基于船舶自动识别系统（Automatic Identification System,AIS）数据表征船舶排放是目前船舶排放空间表征的主流方法,但AIS船舶轨迹点缺失会造成船舶排放量低估和船舶空间分布表征错误,进而影响船舶排放控制区的划分.为改进船舶排放空间表征,本研究以2013年广东省AIS船舶数据为例,采用基于时间和经纬度的三次样条方法对AIS船舶轨迹进行修复,结合动力法计算船舶排放,分析对比AIS轨迹修复前后船舶排放表征的差异,并利用空气质量模型和卫星观测评估AIS轨迹修复对船舶排放表征和广东沿海空气质量模拟的改进效果.结果表明：轨迹修复后广东省海域船舶轨迹点总数由4685773个增至5746664个,船舶NO_x排放量增加了0.6%.对于轨迹点与排放缺失集中的粤东海域,轨迹修复后船舶轨迹点数增加了88%,NO_x排放量在广东省船舶排放量的占比提升至22%,特别是在粤东重点修复海域NO_x排放量增加了2.7倍.原始轨迹在广东省海域较为稀疏,在粤东海域有明显轨迹缺失;轨迹修复后广东省海域船舶轨迹更为密集,粤东海域船舶轨迹得以补充,船舶排放空间分布更连贯.对比模拟结果与卫星观测结果,轨迹修复后粤东重点修复海域船舶模拟浓度与观测浓度的偏差由51%减至6%,总体上船舶排放模拟结果更接近卫星观测结果.     

淮北地区一次春季浮尘天气成因研究

利用激光气溶胶雷达和风廓线雷达,结合卫星遥感资料、地面气象要素资料、大气气溶胶浓度资料和HYSPLIT模型,研究了2017年5月5—8日淮北地区一次沙尘天气过程的特征.结果表明,2017年5月5—6日上午的浮尘(过程1)是由西北-华北地区的远距离输送所致,其中PM_(10)峰值浓度高达766μg·m~(-3),而6日下午—7日的浮尘(过程2)是冷空气回流所导致.外源输入、气象要素和垂直风场的变化为浮尘天气的发生和维持创造了有利条件,降水的出现使本次浮尘天气过程结束.激光气溶胶雷达可以有效监测此次浮尘天气的大气气溶胶消光系数的空间分布,能直观准确地反映出污染物的分布聚集情况以及时空变化,对大气污染监测具有重要意义.本研究还提出了适合江苏地区的浮尘客观判定方法,SO_2/PM_(10)、NO_2/PM_(10)以及PM_(2.5)/PM_(10)的比值可以有效判别浮尘天气.     

Dry deposition of PM10 over the Yellow Sea during Asian dust events from 2001 to 2007

Dry deposition velocities and fluxes of PM10during Asian dust events over the Yellow Sea from 2001 to 2007 were investigated using observation data in Qingdao, China and Jeju, Korea. The dry deposition velocities of PM10 during dust events over the Yellow Sea ranged from 0.19 to 8.17 cm/sec, with an average of 3.38 cm/sec. Dry deposition fluxes of PM10during dust events over the Yellow Sea were in the range of 68.5–2647.1 mg/(m2·day), with an average of 545.4 mg/(m2·day), which is 2–10 times higher than those reported by other studies for both dust and non-dust periods. It was estimated that 2.6 × 1011–48.7 × 1011g dust particles deposit to the Yellow Sea during dust events through dry deposition every year. Compared with the results in previous studies, it was found that the dry deposition of PM10over the Yellow Sea during dust events in the years with high frequency of dust could account for a large or overwhelming fraction of the annual total dry deposition. Backward air mass trajectory analysis showed that dust events influenced Jeju mainly originated from the desert regions located in Mongolia and Inner Mongolia, China. There were 119 backward trajectories influenced both Qingdao and Jeju during 15 dust events from 2001 to 2007, accounting for 61.3% of the total trajectories of 194, indicating that Qingdao and Jeju were usually on the same pathway of dust transport downwind from source areas.     

西安市一次霾过程中气溶胶垂直分布特征及气象要素影响

为探讨西安市典型霾过程中的气溶胶垂直分布特征和气象要素影响,利用地面空气质量数据、CALIPSO卫星激光雷达资料以及气象要素资料,并结合HYSPLIT后向轨迹模式、天气形势分析、相关性分析等,对西安市2016年12月17-21日霾过程依据RH（相对湿度）进行干霾、湿霾和雾霾的划分,并分析不同阶段的气溶胶垂直分布特征.结果表明:前期干霾阶段,西北沙尘的输送使得高空气溶胶退偏比和色比较大,以沙尘型气溶胶为主;中期湿霾阶段,RH的增大使得低层细粒子增多,消光系数达1.7 km-1,以污染型气溶胶为主;后期干霾阶段时,低层大气中非球形粗粒子增多,以混合型气溶胶占主导.气象要素对霾过程影响较大,静风、高湿、"双逆温"效应不利于颗粒物的清除,逆温强度的变化与污染物的消长具有一定的滞后一致性.RH和ρ（PM）共同影响能见度变化,RH高于80%时,能见度由RH主导,相关系数达到-0.871;RH低于80%的污染阶段,ρ（PM）对能见度起主导作用,相关系数达0.85以上.研究显示,不同霾阶段气溶胶垂直分布特征差异较大,气象要素对霾过程的消长有重要影响.      

2014年海口市大气污染物演变特征及典型污染个例分析

主要分析了2014年海口市逐日的空气质量指数(AQI)和6种大气污染物的演变特征,同时,结合卫星遥感和轨迹模式等资料和方法对1次典型污染个例进行诊断.结果表明:海口市2014年的空气质量主要以优和良为主,6 d达到轻度污染级别,1 d达到中度污染(1月5日,AQI值为158).1月污染最为严重,其中,阶段1(1-6日)和阶段3(18-23日)AQI值偏高,阶段2(7-17日)和阶段4(24-31日)偏低.1月东亚地区天气形势演变对海口市AQI值具有动力影响.AQI偏高阶段,地面高压系统位于内蒙古东部,华南低层东北风场有利于污染物向海口市输送;而在AQI偏低阶段,地面高压系统东移出海,低层偏东风场不利于污染物的输送.后向轨迹聚类分析表明,1月海口市比率最大(39%)的气流主要经过大气污染相对严重的广东珠江三角洲(珠三角)地区,有利于污染物的区域传输.污染个例分析表明,海口市污染物浓度变化与气象要素有密切关系,10 m风速较小有助于近地面的污染物在区域内累积,水平风垂直切变偏弱对天气尺度扰动的发展和大气的垂直混合不利.卫星遥感和后向轨迹分析也表明,外源输送与海口市这次大气污染事件有直接关系.     

“2+26”城市2017年冬防减排效果及其潜在原因分析——以衡水市为例

近年来我国大气重污染频发,严重影响民生,其中以京津冀最为严重.2017年"总理基金"启动,同年冬防效果显著.衡水市作为"2+26"城市之一,空气质量排名常年处于倒数十名之内.经过2017年的冬防,空气质量明显改善,衡水市大气污染的改善在"2+26"城市中很具有代表性.本文以衡水作为切入点,利用后向轨迹和浓度权重轨迹分析(CWT)探讨了2017年衡水冬防效果及潜在源区变化,分别从气象轨迹和本地排放初探了潜在原因.结果表明,2017年冬防效果显著,PM_(2.5)浓度降低33%,优良天数增加32 d,重污染天数减少22 d.PM_(10)浓度降低41%,优良天数增加40 d.2017年冬季PM_(2.5)潜在源区由2016年同期衡水北部及以北地区向衡水南部及以南地区转移.PM_(10)潜在源分布变化与PM_(2.5)相似.两年气象条件的对比结果表明,气象变化较小,对潜在源分布影响不大,本地排放是潜在源区分布变化的主要原因,其中衡水北部工业锅炉和扬尘减排量显著高于衡水南部.研究表明,2017年衡水冬防效果显著,相比于气象条件,本地排放对大气颗粒污染及来源影响更大,本研究可为"2+26"城市大气颗粒污染研究提供参考.     

The vertical distribution of aerosols and acid related compounds in air and cloudwater

Vertical profiles (surface to 5 km) of aerosol particle number concentration, NO_y′ mixing ratio, and cloudwater SO₄²⁻ and NO₃⁻ equivalent concentration were obtained in three field studies: North Bay, Ontario, during the summer of 1982 and the winter of 1983–1984, and Syracuse, New York, during the fall of 1984. The measurements from these locations and different seasons are compared. Generally, airborne concentrations are highest with air-mass back trajectories from the south and lowest with back trajectories from the north. For the southerly trajectories, median particle number concentrations (0.2–2 μm) near ground level (950 mb) vary from 1700 cm⁻³ during the summer project to 800 cm⁻³ during the winter project. At 700 mb, the south trajectory particle number concentration ranged between 60 and 170 cm⁻³. Median NO_y′ mixing ratios for southerly back trajectories were approximately 6 and 9 ppb at 950 mb and 0.4 and 0.8 ppb at 700 mb for the fall and winter projects, respectively. Comparison of particle number concentration profiles outside of cloud with cloud droplet plus interstitial aerosol particle number concentrations inside cloud indicate that cumulus clouds can transport aerosols vertically from below cloud base. In contrast, stratiform clouds have similar concentrations inside the clouds as outside at the same altitude. The vertical variations of cloudwater sulphate and nitrate concentrations and the NO₃⁻/SO₄²⁻ equivalent concentration ratio are discussed for each of the three field studies.     

太行山两侧污染物传输对横谷城市气溶胶的影响分析

利用2017~2019年太行山横谷城市阳泉PM₁₀和PM_2.5逐时浓度资料和对应时刻风速风向数据,结合HYSPLIT后向轨迹模型通过聚类分析、潜在源贡献因子和浓度权重轨迹方法分析了横谷城市气流输送特征及对阳泉市气溶胶的影响,并进一步探讨了太行山两侧大气污染物的交换特征.阳泉市气溶胶日变化为单峰单谷型,冬季最高值出现在10：00~11：00,其他季节多在09：00,最小值均在15：00~16：00;月际变化呈1月最高、8月最低.受横谷地形影响,地面风向以偏东风和偏西风频率最高;除小风天气外,春秋季偏西风引起的沙尘天气和冬季偏东风输送也会引起阳泉气溶胶浓度升高;后向轨迹结合污染特征显示,各季节污染轨迹占比为春季26.2%、秋季36.4%和冬季33.7%,主要分布在阳泉的西南和东南区域,冬季在东北区域也有分布;山脉两侧均存在显著的细颗粒物传输,而起源或途经太行山西侧的轨迹粗颗粒物输送亦相对较多;污染轨迹中偏西气流输送对PM₁₀超标率影响更大,偏东气流则主要影响PM_2.5的超标率.不同季节阳泉市气溶胶主要污染潜在源区存在差异,春季为西南和东南两区域;秋季为西南及偏南区域,冬季主要位于偏南和偏东方向区域,山西东南部及与河南北部交界区域是主要的污染贡献源区,太行山两侧通过井陉通道进行大气污染物的相互传输过程显著,其中东向西的PM_2.5传输影响更显著.     

基于风廓线雷达对成都地区典型持续性重污染天气的研究

基于风廓线雷达数据、大气污染数据及气象数据对2017年12月17日—2018年1月3日成都地区的一次持续性重污染天气过程进行研究,并对两次污染物浓度爆发式增长阶段的污染原因及污染物来源进行了分析.结果表明:①在这次重污染天气过程中,风廓线雷达高精度的风场资料(包括水平风速、风向、垂直风速、大气折射率结构常数C■)配合其他气象要素在分析两个污染阶段污染物的累积及扩散、输送中可以发挥重要的作用,即当成都地区水平风场风速较小且风向多变时,此时受静稳型天气控制,污染物浓度会快速累积增长,而当出现较强的东北风时,可能会有沙尘污染物的输入,应注意沙尘天气的提前预警.垂直风场中垂直速度和大气折射率结构常数C■的变化往往影响着污染物浓度的变化,由于风廓线雷达具有较高的时间分辨率,因此,对污染天气过程的变化有一定的指示意义.②结合局地环流指数和边界层通风量,重新定义了一种适合成都地区风场特征的通风指数:有效通风量(EVI),从而表明第一阶段污染的主要原因是成都地区由静稳型天气控制,边界层内风场对污染物的稀释扩散能力差,导致污染物累积.③通过后向轨迹模拟并结合PM_(2.5)浓度数据进行聚类分析,认为第二阶段污染主要是东北方向携带有大量沙尘污染物的气团输送到成都地区导致的,与源于西北地区沙尘天气的沙尘输送密切相关.     

A lagrangian one-layer model of long-range transport of SO2

The daily mean concentrations of SO₂ have been estimated using a simple trajectory model of long-range transport. Seasonal variations in the transformation rate of SO₂ to sulphate are assumed. The mixing height varied from day to day depending on the stability conditions. The dry deposition velocity above the ground varies according to the season, cloud cover and time of day, while a constant value is applied above the sea. Under present model assumptions the variation of pollutant concentration with time at the receptor point arises only due to variable meteorological conditions. During the test period measured concentrations were often higher than estimated. However, the order of magnitude of pollutant concentration was well predicted. In future work, input meteorological data should have a finer resolution. Further, better parameterizations of sulphur dioxide concentrations at the start points of trajectories and wet deposition should be employed.     

Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015

Trajectory clustering, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods were applied to investigate the transport pathways and identify potential sources of PM_2.5 and PM₁₀ in different seasons from June 2014 to May 2015 in Beijing. The cluster analyses showed that Beijing was affected by trajectories from the south and southeast in summer and autumn. In winter and spring, Beijing was not only affected by the trajectories from the south and southeast, but was also affected by trajectories from the north and northwest. In addition, the analyses of the pressure profile of backward trajectories showed that backward trajectories, which have important influence on Beijing, were mainly distributed above 970 hPa in summer and autumn and below 950 hPa in spring and winter. This indicates that PM_2.5 and PM₁₀ were strongly affected by the near surface air masses in summer and autumn and by high altitude air masses in winter and spring. Results of PSCF and CWT analyses showed that the largest potential source areas were identified in spring, followed by winter and autumn, then summer. In addition, potential source regions of PM₁₀ were similar to those of PM_2.5. There were a clear seasonal and spatial variation of the potential source areas of Beijing and the airflow in the horizontal and vertical directions. Therefore, more effective regional emission reduction measures in Beijing''s surrounding provinces should be implemented to reduce emissions of regional sources in different seasons.     

A fast long-range transport model for operational use in episode simulation. Application to the Chernobyl accident

A simple Lagrangian puff trajectory model and its software implementation, STRALE, are described. Standard meteorological data are used as input for the simulation of the three-dimensional atmospheric transport and dispersion of a pollutant released by a point source. The schemes adopted to describe the vertical diffusion and the interaction with the mixing layer are discussed on the basis of the comparison between simulated and measured ¹³⁷Cs activities for the Chernobyl nuclear accident.     

我国春季沙尘暴研究

利用GMS卫星遥感资料,结合地面气象观测资料和中尺度每小时数值模拟,对1998年4月和2000年4月发生的强沙尘大气演变过程进行了详细的分析,初步确定了影响我国的沙尘暴起始源地,并将我国的沙尘暴天气划分为U变化型（停滞型）和移动型（锋面气旋型等）．详细分析了低涡型沙尘暴和东北低涡型沙尘暴的发生、发展的宏观机制     

MODIS 3 km气溶胶光学厚度产品检验及其环境空气质量指示

分析了MODIS C006 3 km卫星遥感气溶胶产品的算法流程,并与AERONET观测数据进行对比验证,综合新疆阿克苏地区地面空气子站1年的颗粒物质量浓度(PM10)、环境气象资料(能见度、湿度等),评估了该高分辨率气溶胶产品的精度和稳定性.分析表明,MODIS 3 km AOD与AERONET地基AOD(Issyk-Kul)的相关系数(r)达到0.8836,满足期望误差要求,但存在高估;研究区AOD和PM10存在同步变化趋势,新疆阿克苏市区2个空气子站PM10质量浓度与AOD的相关系数(r)均大于0.55,直接对比的相关性好于类似研究;经高度订正和湿度订正后AOD-PM10的相关系数和拟合优度均有所提高,标准误差和变异系数均下降,但提升并不明显.这一相关性结果与研究区本底气象环境条件有关.MODIS 3 km AOD的季平均结果表明,阿克苏地区AOD存在显著的季节性变化,春季明显高于其他季节,主要城市春季平均AOD在1.5以上,夏季和秋季AOD均值基本介于0.6~0.7之间,阿克苏市主城区夏秋季AOD季均值仍在1.0以上,反映人口集聚、城市交通工业发展等大气人为污染的增加导致AOD的增高.结果表明,MODIS C006 3 km AOD产品质量稳定,其月、季平均等长时间尺度结果有更好的空间覆盖,可满足区域环境空气质量评估的需要.     

Observations of atmospheric pollutants at Lhasa during 2014–2015: Pollution status and the influence of meteorological factors

Atmospheric pollutants including SO₂, NO₂, CO, O₃ and inhalable particulate matter (PM_2.5 and PM₁₀) were monitored continuously from March 2014 to February 2015 to investigate characteristics of air pollution at Lhasa, Tibetan Plateau. Species exhibited similar seasonal variations except O₃, with the peaks in winter but low valleys in summer. The maximum O₃ concentration was observed in spring, followed by summer, autumn, and winter. The positive correlation between O₃ and PM₁₀ in spring indicated similar sources of them, and was assumed to be turbulent transport. Temperature was the dominant meteorological factor for most species in spring. High temperature accelerates O₃ photochemistry, and favors air disturbance which is conductive to dust resuspension in spring. Relative humidity (RH) and atmospheric pressure were the main meteorological factors in summer. RH showed negative correlations with species, while atmospheric pressure posed opposite situation. Wind speed (WS) was the dominant meteorological factor in autumn, the negative correlations between WS and species indicated diffusion by wind. Most species showed non-significant correlations with meteorological factors in winter, indicating the dependence of pollution on source emission rather than restriction by meteorology. Pollution weather character indicated that emissions were from biomass burning and dust suspension, and meteorological factors also played an important role. Air stream injection from the stratosphere was observed during O₃ pollution period. Air parcels from Southwest Asia were observed during air pollution period in winter. An enhancement in air pollutants such as O₃ would be expected in the future, more attention should be given to countermeasures for prevention of air pollution in the future.