Nocturnal Low-level Winds and Their Impacts on Particulate Matter over the Beijing Area

Three-month wind profiles, 260 m PM1 concentrations [i.e., particulate matter (PM) with an aerodynamic diameter ≤ 1 μm], and carrier-to-noise ratio data at two Beijing sites 55 km apart (urban and suburban) were collected to analyze the characteristics of low-level nocturnal wind and PM in autumn and winter. Three mountain-plain wind events with wind shear were selected for analysis. The measurements indicated that the maximum wind speeds of the northerly weak low-level jet (LLJ) below 320 m at the suburban site were weaker than those at the urban site, and the LLJ heights and depths at the suburban site were lower than those at the urban site. The nocturnal 140 m mean vertical velocities and the variations in vertical velocity at the urban site were larger than those at the suburban site. A nocturnal breeze with a weak LLJ of ～3 m s-1 noticeably offset nocturnal PM transport due to southerly flow and convergence within the northern urban area of Beijing. Characteristics of the nocturnal LLJ, such as start-up time, structure, intensity, and duration, were important factors in determining the decrease in the nocturnal horizontal range and site-based low-level variations in PM.     

北京地区气溶胶PM2.5粒子浓度的相关因子及其估算模型

文中运用统计分析和气象统计预报的方法 ,使用北京白石桥小区的污染物观测资料和同期北京地区的气象观测资料 ,对影响大气污染的气象因子进行了综合分析 ,并分别建立了气溶胶PM 2 .5粒子浓度与气体污染物、气象要素场的两类统计相关拟合模型。发现气溶胶PM2 .5粒子浓度与气体污染物浓度存在不同程度的相关性 ,且与气象条件亦存在显著的相关关系 ,此类时空变化及其量化估算模型具有一定实际应用价值。通过确定气象要素场和气溶胶浓度的关系可进一步研究不同地区的污染物输送和污染源扩散影响的问题。     

北京地区夏末秋初气象要素对PM2.5污染的影响

利用北京宝联站及北京上甸子大气本底站2006—2008年的7—9月PM_2.5连续观测资料以及北京市观象台的探空数据、海淀气象站的风廓线雷达和降水量等资料,对北京地区夏末秋初PM_2.5的质量浓度特征及其与气象要素的关系进行了统计分析。结果表明:城区站各月平均PM_2.5质量浓度明显高于郊区站,高空偏南气流的输送是造成城区及本底地区出现细颗粒物污染的主要原因。从地面风速来看,城区当北风和南风分别达到2 m·s-1和3.5 m·s-1以上时能起到扩散作用;郊区在低风速的北风条件下也能起到扩散和稀释作用,而南风基本上对郊区的颗粒物无扩散作用。PM_2.5质量浓度在降水前后的清除量与降水量、初始质量浓度均呈正相关关系,城区及郊区的云下清除过程更多取决于降水前污染物的浓度,降水量作用较弱。当混合层高度突破1500 m时,垂直扩散对污染物的稀释扩散效果明显。     

淄博市污染气象特征与大气环境容量

利用淄博市环境监测站2002-2004年间的主要大气污染物浓度和同期气象资料,综合分析了淄博市大气环境污染状况及演变特征,用A-P值法对大气环境容量进行测算.结果表明该市主要污染物为可吸入颗粒物(PM10)和二氧化硫(SO2),其实际排放量均高于理想大气环境容量.此外,引入美国NOAA后向轨迹模式(HYSPLIT4),分析了影响淄博市强污染天气的外来气团,确认它们是源于东北地区和内蒙古东部的偏北气流,以及蒙古国中部的偏西气流.这些结果为今后制定城市发展规划,控制和防治大气污染提供了科学依据.     

青岛一次沙尘污染事件的气象条件特征

2008年5月28日至6月1日青岛市区出现了持续5 d的大气污染,其中29-30日为重度污染,其余3日为轻度污染。本文基于青岛常规地面和高空观测资料以及环境监测站SO2、NO2、PM10监测资料,利用资料分析和中尺度数值模拟的方法,分析造成青岛此次持续多日的大气污染的污染源、大气环流和气象要素特征。分析结果表明：此次污染过程主要是外来沙尘引起的PM10污染;持续较强的逆温层结以及近地面层弱南北风频繁交替出现造成沙尘在近地层往复、积聚,最终导致连续多日的空气污染。     

Surface Trace Gases at a Rural Site between the Megacities of Beijing and Tianjin

The North China Plain （NCP） has recently faced serious air quality problems as a result of enhanced gas pollutant emissions due to the process of urbanization and rapid economic growth. To explore regional air pollu- tion in the NCP, measurements of surface ozone （O3）, nitrogen oxides （NOx）, and sulfur dioxide （SO2） were car- ried out from May to November 2013 at a rural site （Xianghe） between the twin megacities of Beijing and Tianjin. The highest hourly ozone average was close to 240 ppbv in May, followed by around 160 ppbv in June and July. High ozone episodes were more notable than in 2005 and were mainly associated with air parcels from the city cluster in the hinterland of the polluted NCP to the southwest of the site. For NOx, an important ozone precur- sor, the concentrations ranged from several ppbv to nearly 180 ppbv in the summer and over 400 ppbv in the fall. The occurrence of high NOx concentrations under calm condi- tions indicated that local emissions were dominant in Xianghe. The double-peak diurnal pattern found in NOx concentrations and NO/NOx ratios was probably shaped by local emissions, photochemical removal, and dilution re- sulting from diurnal variations of surface wind speed and the boundary layer height. A pronounced SO2 daytime peak was noted and attributed to downward mixing from an SO2-rich layer above, while the SO2-polluted air mass transported from possible emission sources, which differed between the non-heating （September and October） and heating （November） periods, was thought to be responsible for night-time high concentrations.     

Oscillation of Surface PM<Subscript>2.5</Subscript> Concentration Resulting from an Alternation of Easterly and Southerly Winds in Beijing: Mechanisms and Implications

We used simultaneous measurements of surface PM_2.5 concentration and vertical profiles of aerosol concentration, temperature, and humidity, together with regional air quality model simulations, to study an episode of aerosol pollution in Beijing from 15 to 19 November 2016. The potential effects of easterly and southerly winds on the surface concentrations and vertical profiles of the PM_2.5 pollution were investigated. Favorable easterly winds produced strong upward motion and were able to transport the PM_2.5 pollution at the surface to the upper levels of the atmosphere. The amount of surface PM_2.5 pollution transported by the easterly winds was determined by the strength and height of the upward motion produced by the easterly winds and the initial height of the upward wind. A greater amount of PM_2.5 pollution was transported to upper levels of the atmosphere by upward winds with a lower initial height. The pollutants were diluted by easterly winds from clean ocean air masses. The inversion layer was destroyed by the easterly winds and the surface pollutants and warm air masses were then lifted to the upper levels of the atmosphere, where they re-established a multi-layer inversion. This region of inversion was strengthened by the southerly winds, increasing the severity of pollution. A vortex was produced by southerly winds that led to the convergence of air along the Taihang Mountains. Pollutants were transported from southern–central Hebei Province to Beijing in the boundary layer. Warm advection associated with the southerly winds intensified the inversion produced by the easterly winds and a more stable boundary layer was formed. The layer with high PM_2.5 concentration became dee-per with persistent southerly winds of a certain depth. The polluted air masses then rose over the northern Taihang Mountains to the northern mountainous regions of Hebei Province.     

2007和2008年夏季北京奥运馆大气PM10与PM2.5质量浓度变化特征

为了监测北京奥运主场馆附近大气颗粒物的污染状况以及评估奥运污染源减排措施对北京大气颗粒物质量浓度变化的影响,利用颗粒物在线监测仪器TEOM于2007年和2008年夏季,在奥运主场馆附近的中国科学院遥感应用研究所办公楼楼顶对大气颗粒物PM10和PM2.5进行了连续同步观测。结果表明,2007年夏季监测点附近大气PM10与PM2.5质量浓度的平均值分别为153.9和71.2μg.m-3,而2008年夏季PM10与PM2.5质量浓度的平均值分别为85.2和52.8μg.m-3。与奥运前一年同时段相比,奥运时段大气PM10和PM2.5的质量浓度分别下降44.5%和25.1%。对比分析奥运前后的2次典型污染过程发现,空气相对湿度的增加和偏南气流输送的共同影响易造成大气颗粒物的累积增长,而降雨的湿清除作用和偏北气流则会使大气颗粒物浓度迅速降低。在相近的气象条件下,奥运前后的污染过程中,大气细粒子的日均增长速率分别为25.1和13.9μg.m-3.d-1,而大气粗粒子的日均增长速率分别为20.8和2.2μg.m-3.d-1,奥运时段污染累积过程中大气粗、细粒子的增长速率分别显著低于和略低于奥运前同时段污染过程中颗粒物的增长速率。污染源减排措施的实施是奥运期间大气颗粒物质量浓度降低的主要原因,从控制效果来看,奥运期间实施的污染源减排措施对大气粗粒子的控制效果明显好于大气细粒子。     

Reductions of PM<Subscript>2.5</Subscript> in Beijing-Tianjin-Hebei urban agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics.The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period(1 June-30 October 2008).The PM2.5 mass concentrations were 53 μg m 3,66 μg m 3,and 82 μg m 3 at the background site,in Beijing,and in the Beijing-Tianjin-Hebei urban agglomerations,respectively.The PM2.5 levels were lowest during the 2008 Olympic Games(8-24 August):35 μg m 3 at the background site,42 μg m 3 in Beijing and 57 μg m 3 in the region.These levels represent decreases of 49%,48%,and 56%,respectively,compared to the prophase mean concentration before the Olympic Games.Emission control measures contributed 62%-82% of the declines observed in Beijing,and meteorological conditions represented 18%-38%.The concentration of fine particles met the goals set for a "Green Olympics."     

春节期间北京地区交通出行规律对热岛效应和大气污染的影响

利用北京地区2006—2015年春节及其前后三周的城区、郊区站数据分析了早晚高峰期出行活动对城市热岛效应、NO_x浓度、PM_2.5浓度的影响。结果表明人口、交通、社会活动的密集程度的确会对城市热岛效应和大气污染物浓度造成一定的影响:(1)第-3、-2、+2、+3周(以下称"BG时段")与春节周(以下称"CNY时段")间的城市热岛效应差异在早高峰期间平均为0.30℃,在晚高峰期间平均为0.43℃,在其他时段平均为0.26℃,晚高峰对城市热岛效应的影响更明显;(2)BG时段与CNY时段城、郊NO_x浓度差的最大差异出现在08时,为54.95μg/L。在早高峰期间为48.55μg/L,晚高峰期间为23.44μg/L。城市晚高峰出行活动对NO_x浓度城、郊差异的贡献量随着夜间的不利扩散条件而延迟出现峰值,城市早高峰出行对NO_x浓度城、郊差异的增大作用更为突出;(3)城郊PM_2.5浓度BG时段高于CNY时段的时间出现在05—19时,早高峰期间平均差值为12.82μg/m³,晚高峰期间平均差值为8.22μg/m³。考虑到汽车尾气中的超细粒子和污染气体需要在空气中进行化学反应或者吸湿增长才能变成PM_2.5,因此PM_2.5浓度的变化情况并不完全对应于早晚高峰出行的时间,而是有所延迟。     

周边气象条件对南京城区大气污染物浓度的影响

针对2014年8月南京国际青年奥林匹克运动会期间周边地区污染源的减排控制研究,本文将2010-2012年8月的NCEP/NCAR 的6 h再分析资料作为驱动场,利用WRF模式处理得到时空尺度更为精细的风场资料,结合南京奥体中心观测点的颗粒物及气体污染物浓度资料,通过相关分析以及合成分析,诊断得到了8月影响南京地区主要污染物的周边源区及其关键输送通道。结果表明：尽管8月青奥会时段南京地区主导风为海洋吹向大陆的东南风,但影响南京地区主要污染物（SO₂,NO₂,PM₁₀）浓度的外源及其主要输送路径各有不同。来自于南京西南部江西、湖南、湖北等地区的较远距离输送是对南京地区SO₂浓度影响的关键通道;来自于南京正南方向（安徽、浙江一带）的近距离输送是对南京地区NO₂浓度影响的关键通道;来自于南京西南部（湖北一带）的中远距离输送是对南京地区PM₁₀浓度影响的关键通道。     

几种空气质量预报方法的预报效果对比分析

目前应用于我国各个城市空气质量预报业务的预报方法主要有三种 :数值模式预报、统计预报和综合经验预报。这几种预报方法都有其各自的优势 ,同时也存在一些不足。应用以上方法对天津市市区进行空气质量业务预报 ,通过实测资料与预报结果进行对比分析 ,给出这几种方法在天津市区空气质量预报中的预报效果客观评价。     

北京市房山区大气污染物时空分布特征及气象影响因素分析

利用北京市房山区良乡镇和琉璃河镇内的区域自动气象站和环境监测站观测数据,对2013年至2015年PM_(2. 5)、PM_(10)、NO_2、SO_2、CO 5种大气污染物浓度变化特征进行了统计分析。结果显示,近3年来,两个镇综合污染物指数呈现逐年下降趋势,各污染物对房山区整体大气污染的贡献率从大至小依次为PM_(2. 5)、PM_(10)、SO_2、NO_2、CO,PM_(2. 5)已取代传统大气污染物SO_2成为房山区的主要大气污染贡献体。两个站点各污染物浓度均表现出明显的季节、月、日变化特征。在不同季节条件下,局地气象要素与污染天气发生概率之间有着很好的相关关系。因此,可根据气象要素分级方法找出各季节污染天气发生时最敏感的气象因素,为局地污染天气预报提供参考指标,也为防范空气污染、制定科学的综合管理措施提供科学参考。     

北京两次重污染沙尘天气成因及动力传输特征的对比研究

应用气象、空气质量和ERA-Interim再分析资料,结合HYSPLIT后向轨迹模型和地理信息,对比分析了2018年北京两次重污染沙尘天气的成因、传输特征及影响要素等。结果表明:两次过程的沙尘源地均为蒙古国,但3月28日沙尘天气由蒙古气旋引发,传输出现折向,以东北和偏东两条路径输送入京,5月28日沙尘受低涡和发展的低压冷锋影响,为典型的西北传输路径;高空的引导气流与低层冷空气的强度以及地形是导致沙尘传输出现显著差异的主要影响因素;高空为偏西气流,低层冷平流较弱,受到山脉的阻挡,沙尘气团东移至地势较低的区域后,在气压梯度力的驱动下传输方向发生转折,以偏东路径绕流进入北京;高空的偏北气流和低层冷平流较强,沙尘气团可直接翻越山脉从西北路径入京,沙尘粒子的运移高度相对较高。     

2008年北京奥运会期间污染控制效果数值模拟——以个例分析为例

利用2007和2008年北京地区空气质量监测资料和NCEP再分析资料,分析了北京地区空气动力学当量直径小于等于10μm颗粒物(PM10)污染过程与天气形势及天气系统之间的关系。结果表明:西太平洋热带气旋路径对北京地区发生PM10污染具有预示作用,即当热带气旋北上并在朝鲜半岛或日本登陆的情况下,北京地区一般受持续均压场等弱中尺度天气系统控制,这种中尺度天气系统不利于污染物的扩散,因此北京地区经常发生区域性的PM10空气污染事件。在2007年9次台风北上登陆朝鲜半岛或日本的过程中,北京地区伴随发生了9次PM10污染过程,预示准确率达100%,2008年的预示准确率也达到了80%以上。为了说明北京奥运会期间污染控制措施对改善北京空气质量有实际效果,利用中国科学院大气物理研究所区域空气质量模式NAQPMS,采用无控制措施源和有控制措施源,对2008年北京残奥会期间一次西太平洋北上型热带气旋天气条件下的空气质量状况进行了数值模拟试验,揭示了此次过程北京地区未发生PM10空气污染的原因。     

Changes in air pollutants during the COVID-19 lockdown in Beijing:Insights from a machine-learning technique and implications for future control policy

基于2015-2020年北京35个环境空气站和20个气象站观测资料,应用机器学习方法(随机森林算法)分离了气象条件和源排放对大气污染物浓度的影响.结果发现,为应对疫情采取的隔离措施使北京2020年春节期间大气污染物浓度降低了35.1％-51.8％;其中,背景站氮氧化物和一氧化碳浓度的降幅最大,超过了以往报道较多的交通站点.同时,2020年春节期间的气象条件不利于污染物扩散,导致多次霾污染事件发生.为进一步改善北京空气质量,未来需要优化减排策略.     

长江三角洲地区四省会城市PM10污染特征

对长江三角洲地区四省会城市(上海、南京、杭州、合肥)2001-2005年逐日大气污染指数资料进行统计分析,并采用HYSPLIT轨迹模式,分析了各城市中度以上大气污染过程的输送特征。结果表明:2002年以后,四省会城市的大气质量都有好转的趋势;大气污染发生频率最高的季节是春季(南京)和冬季(其他城市);11月和3月是大气污染出现频率最高的月份。上海PM10与NO2和SO2浓度之间存在非常显著的正相关,合肥PM10与NO2和SO2浓度之间的相关性比上海略差。两城市都是PM10与NO2之间的偏相关系数远大于与SO2之间的偏相关系数。各城市的PM10浓度都与另外三个城市之间存在显著的正相关,尤其是3,4月份。后向轨迹分析表明,造成本地区中度以上大气污染的气团以西北来向为主。     

On large-scale transport of dust storms and anthropogenic dust-falls over east Asia observed in central Korea in 2009

Dust air pollution has been routinely monitored in central Korea for the last two decades. In 2009, there were eight typical episodes of significant dust loadings in the air: four were caused by dust storms from deserts in Mongolia and Northern China, while the remaining were typical cases of anthropogenic air pollution masses arriving from the Yellow Sea and East China. These natural dust loadings occurred with cool northwesterly airflows in the forward side of an intense anticyclone coming from Mongolia and Siberia. The mean concentrations of the four natural dustfall cases for TSP, PM10 and PM2.5 were 632, 480 and 100 μg m^?3, respectively. In contrast, the anthropogenic dust-pollution episodes occurred with the warm westerly and southwesterly airflows in the rear side of an anticyclone. This produced a favorable atmospheric and chemical condition for the build-up of anthropogenic dust air pollution in the Yellow Sea. The mean concentrations of the four anthropogenic dust loadings for TSP, PM10 and PM2.5 were 224, 187 and 137 μg m^?3, respectively. The contents of fine dust loadings of PM2.5 were comparatively high in the cases of anthropogenic air pollution. High atmospheric concentrations of fine particles in the atmosphere cause poor visibility and constitute a health hazard. Satellite observations clearly showed the movement of dust-pollution masses from Mongolia and Northern China and from the Yellow Sea and East China that caused these dust pollution episodes in Korea.     

Regional meteorological patterns for heavy pollution events in Beijing

The present study investigates meteorological conditions for the day-to-day changes of particulate matter (PM) concentration in Beijing city during the period 2008–2015. The local relationship of PM concentration to surface air temperature, pressure, wind speed, and relative humidity displays seasonal changes and year-to-year variations. The average correlation coefficient with PM₁₀ in spring, summer, fall, and winter is 0.45, 0.40, 0.38, and 0.30 for air temperature; –0.45, –0.05, –0.40, and –0.45 for pressure; 0.13, 0.04, 0.53, and 0.50 for relative humidity; and –0.18, –0.11, –0.45, and –0.33 for wind speed. A higher correlation with wind speed is obtained when wind speed leads by half a day. The heavily polluted and clean days, which are defined as the top and bottom 10% of the PM values, show obvious differences in the regional distribution of air temperature, pressure, and wind. Polluted days correspond to higher air temperature in all the four seasons, lower sea level pressure and anomalous southerly winds to the south and east of Beijing in spring, fall, and winter, and a northwest–southeast contrast in the pressure anomaly and anomalous southerly winds in summer. Higher relative humidity is observed on polluted days in fall and winter. The polluted days are preceded by an anomalous cyclone moving from the northwest, accompanied by lower pressure and higher air temperature, in all four seasons. This feature indicates the impacts of moving weather systems on local meteorological conditions for day-to-day air quality changes in Beijing.     

Distribution and source apportionment of Polycyclic aromatic hydrocarbons from atmospheric particulate matter PM<Subscript>2.5</Subscript> in Beijing

A total of 11 PM2.5 samples were collected from October 2003 to October 2004 at 8 sampling sites in Beijing city. The PM2.5 concentrations are all above the PM2.5 pollution standard （65 μg m^-3） established by Environmental Protection Agency, USA （USEPA） in 1997 except for the Ming Tombs site. PM2.5 concentrations in winter are much higher than in summer. The 16 Polycyclic aromatic hydrocarbons （PAHs） listed as priority pollutants by USEPA in PM2.5 were completely identified and quantified by high performance liquid chromatography （HPLC） with variable wavelength detector （VWD） and fluorescence detector （FLD） employed. The PM2.5 concentrations indicate that the pollution situation is still serious in Beijing. The sum of 16 PAHs concentrations ranged from 22.17 to 5366 ng m^-3. The concentrations of the heavier molecular weight PAHs have a different pollution trend from the lower PAHs. Seasonal variations were mainly attributed to the difference in coal combustion emission and meteorological conditions. The source apportionment analysis suggests that PAHs from PM2.5 in Beijing city mainly come from coal combustion and vehicle exhaust emission. New measures about restricting coal combustion and vehicle exhaust must be established as soon as possible to improve the air pollution situation in Beijing city.