Chemical characterization of fine particulate matter during peak PM10 episodes in Apulia (South Italy)

Some peak PM10 episodes, occurred during PM monitoring campaigns performed on October 2005 and February and June 2006 in Bari town, have been characterized. Moreover back trajectories of air masses and Principal Component Analyses were applied. Three of the peak PM10 episodes investigated were related to local emissions of primary pollutants during poor atmospheric dispersion conditions. The other two peak PM10 episodes considered are related with long range transport air masses toward Apulia region: in one case the chemical characterization and the back trajectories analysis indicate that high PM10 value detected is due to the Saharan dust advection in the Apulia region; in the other case air masses with different origin give rise to high PM10 value.Moreover PM10 daily mean concentrations, presented in this paper collected from January 2005 to August 2007 and obtained by automatic device in six stations of air quality monitoring networks in Bari territory, do not show a seasonal trend for PM10 concentrations, contrary to the PM10 trend shown in the towns of North Italy. This can be explained mostly considering that our region presents generally meteo-climatic conditions that favour pollutants dispersion.     

合肥市PM10 输送轨迹分类研究

应用聚类分析的方法,对2001—2005年合肥市逐日72 h后向轨迹按季节分类,结合PM10日均浓度观测资料,分析了不同输送轨迹与该地区PM10浓度之间的关系。结果表明:不同方向后向轨迹所对应的PM10平均浓度有明显不同;最高PM10平均浓度对应的后向轨迹在春、秋和冬季都是来自西北方向,它们与季节平均的相对距平分别为44%,20%和31%;夏季为东北方向,与季节平均的相对距平为20%;其次为本地轨迹,各季的相对距平分别为5%,16%,18%和17%。根据分析得出合肥地区6组易于出现高浓度PM10的后向轨迹及对应的天气形势,并简要分析了其特征。气溶胶的远程输送主要发生在自由大气层,区域输送主要发生在边界层内。合肥地区大气污染事件超过50%与远程输送有关。移动快的气团不一定对应低浓度的PM10。     

Characterization of particulate matter in the Apulia Region (South of Italy): features and critical episodes

The chemical composition of PM₁₀ and PM_2.5 samples collected during two seasonal monitoring campaigns at residential, urban and industrial Apulia Region- sites was investigated. Ionic fraction, carbonaceous compounds and Polycyclic Aromatic Hydrocarbons were determined for all samples. High correlations among PM data collected in the investigated sites suggested the regional character of particulate matter. It was also confirmed by five days back trajectories analysis. Moreover, no significant seasonal trend in PM mass concentration was observed in the investigated sites. These results, relevant for the area under investigations, were not observed in the North of Italy and Europe and allow to conclude that PM₁₀ and PM_2.5 cannot be considered ‘good’ indicators for the evaluation of local anthropic contributions to air quality. On the contrary, the high levels of Polycyclic Aromatic Hydrocarbons found in Taranto sampling sites suggested that PAHs can be a better indicator for this purpose. This result is also relevant in order to weigh the importance of industrial area and to suggest right policy control to decision makers.     

Impact of Saharan dust on PM10 concentration in the Mediterranean Tunisian coasts

This paper presents samples of Saharan dust outbreak affecting the Mediterranean Tunisian coasts and its impact on PM10 (Particles with an aerodynamic diameter below 10 µm) surface concentrations measured at seven monitoring stations during summer 2006. During the events, the daily PM10 levels at all stations exceeded EU and Tunisian air quality standard limits which are equal to 50 µg/m³. The maximum values ranged from 200 µg/m³ to 300 µg/m³ depending on the monitoring station. The impact is even more dramatic on PM10 hourly concentrations leading to maximum hourly peaks ranging from 400 µg/m³ to 850 µg/m³ again depending on the monitoring station (industrial or residential, traffic and commercial). Comparison between backward air masses trajectories reaching Tunisian coasts and satellite imageries vis-à-vis the PM10 hourly concentrations measured at the monitoring stations during 2006 evidenced the influence of the Saharan dust outbreaks on surface concentrations. The origin of the air masses is found to be from South-West direction under the influence of air masses from the Algerian Saharan desert.     

Satellite and ground observations for large-scale air pollution transport in the Yellow Sea region

Large-scale air pollution transport (LSAPT) in the Yellow Sea region and their inflow onto the Korean Peninsula were observed through satellite images and ground measurements. LSAPT includes regional continental air-masses saturated with pollutants originating from China and subsequently landing on or passing through the Korean Peninsula. It is also possible to identify the distribution and transport patterns of LSAPT over the Yellow Sea. The ground concentrations for PM10, PM2.5 and CO measured at Cheongwon, located in the centre of south Korea, were compared with NOAA satellite images. Notably, the episodes observed of the LSAPT show a PM2.5 to PM10 ratio of 74% of the daily maximum concentrations. However, cases of duststorms were clearly distinguished by much higher PM10 concentrations and a ratio of 30% of PM2.5 to PM10 for daily maximum concentrations. For the episode on January 27, 2006, the inflow of a regionally polluted continental air-mass into the central and southwestern regions of the Korean Peninsula was observed sequentially at various ground observatories as well as by satellite. The north airflow dissipated the clouds over Mt. Halla on Jeju Island and further downwind, reducing air pollution and creating a von Kármán vortex.     

郑州市空气质量统计预报方法探讨

根据2005年、2006年采暖期RegCM 3模式输出产品和郑州市环境监测中心逐日监测资料,利用逐步回归方法建立了PM10、SO2、NO2等污染物质量浓度预报方程。该方法在2007年采暖期的试报中效果不理想,预报准确率明显低于历史拟合率。为了提高预报准确率,针对目前采用的统计方法中存在的不足,即在选择预报因子时没有考虑预报因子之间的相关性,挑选的预报因子由于非正交,使回归计算的结果不稳定。将自然正交分解和多元回归分析结合起来,以采暖期各污染物的日均质量浓度为预报对象,建立预报模型。结果表明,采用新方法制作的空气质量预报准确率有一定程度提高。     

Local and regional sources of fine and coarse particulate matter based on traffic and background monitoring

The aim of this study was to identify local and exogenous sources affecting particulate matter (PM) levels in five major cities of Northern Europe namely: London, Paris, Hamburg, Copenhagen and Stockholm. Besides local emissions, PM profile at urban and suburban areas of the European Union (EU) is also influenced by regional PM sources due to atmospheric transport, thus geographical city distribution is of a great importance. At each city, PM₁₀, PM_2.5, NO₂, SO₂, CO and O₃ air pollution data from two air pollution monitoring stations of the EU network were used. Different background characteristics of the selected two sampling sites at each city facilitated comparisons, providing a more exact analysis of PM sources. Four source apportionment methods: Pearson correlations among the levels of particulates and gaseous pollutants, characterisation of primal component analysis components, long-range transport analysis and extrapolation of PM size distribution ratios were applied. In general, fine (PM_2.5) and coarse (PM₁₀) particles were highly correlated, thus common sources are suggested. Combustion-originated gaseous pollutants (CO, NO₂, SO₂) were strongly associated to PM₁₀ and PM_2.5, primarily at areas severely affected by traffic. On the contrary, at background stations neighbouring important natural sources of particles or situated in suburban areas with rural background, natural emissions of aerosols were indicated. Series of daily PM_2.5/PM₁₀ ratios showed that minimum fraction values were detected during warm periods, due to higher volumes of airborne biogenic PM coarse, mainly at stations with important natural sources of particles in their vicinity. Hybrid single-particle Lagrangian integrated trajectory model was used, in order to extract 4-day backward air mass trajectories that arrived in the five cities which are under study during days with recorded PM₁₀ exceedances. At all five cities, a significantly large fraction of those trajectories were classified in short- and medium-range clusters, thus transportation of particulates along with slow moving air masses was identified. A finding that supports the assumption of long-range transport is that, at background stations, long-range transportation effects were stronger, in comparison to traffic stations, due to less local particle emissions. Short-range trajectories associated to PM transport in Stockholm, Copenhagen and Hamburg were mainly of a continental origin. All three cities were approached by slow moving air masses originated from Poland and the Czech Republic, whereas Copenhagen and Stockholm were also influenced by short-range trajectories from Germany and France and from Jutland Peninsula and Scandinavian Peninsula, respectively. London and Paris are located to the north-west part of Europe. Trajectories of short and medium length arrived to these two megacities mainly through France, Germany, UK and North Atlantic.     

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.     

银川市主要污染物变化特征及其关系研究

利用2013-2019年银川市主要污染物浓度数据,分析了近年来银川市主要污染物浓度变化特征,并运用主成分分析法对主要污染物之间的关系进行研究。结果表明：近年来银川市主要污染物浓度除O₃逐年呈上升趋势外,其他均呈下降趋势;市区站O₃浓度较郊区背景站低,其他污染物市区较郊区背景站高;市区站PM₁₀和PM_2.5浓度超国家二级标准;除O₃浓度夏季高,冬季低外,其他污染物冬季高,夏季低;CO、NO₂、PM₁₀、PM_2.5浓度呈"双峰型"日变化特征,O₃和SO₂呈"单峰型"日变化特征。银川市主要污染物NO₂浓度与CO和O₃相关性显著,PM₁₀和PM_2.5之间相关性显著;污染物第一主成分是NO₂、CO和O₃,方差贡献率达到50%以上,加之银川市O₃浓度逐年呈升高趋势,表明近年来银川市大气光化学污染增加。     

南京SO2、NO2和PM10变化特征及其与气象条件的关系

利用南京市2002—2006年大气监测资料,分析了南京市大气中SO2、NO2、PM10年变化趋势及月季规律,评价了南京市空气质量状况。结果表明:5a来,SO2质量浓度呈显著上升趋势,NO2质量浓度缓慢上升,PM10质量浓度明显下降;南京市首要污染物是PM10,SO2、NO2污染较轻;3种污染物质量浓度均以夏季最低。进一步研究不同气象条件下污染物质量浓度发现,污染物质量浓度与风速反相关,且东南风时浓度最高;降水对污染物有清除作用;雾、霾天气下污染加剧;气象能见度与PM10、NO2的质量浓度反相关;污染物有明显的"周末效应",周末质量浓度值较低。     

喀什地区浮尘天气特征及一次重污染天气成因分析

根据1961—2018年喀什地区9个国家站浮尘日数逐日观测资料,利用气候学统计、M-K突变检验等方法分析喀什地区浮尘日数的时空分布等气候特征,分析2019年3月19—25日喀什地区出现的强浮尘造成的重污染天气成因。结果表明:喀什地区年平均浮尘日数为71 d,浮尘日数总体呈减少趋势,并于1997年前后发生了显著减少性突变。2019年3月19—25日出现的强浮尘天气过程,持续时间长,影响范围广,乌拉尔山高压脊发展,脊前横槽转竖,在新疆东部回流东灌冷空气是造成此次沙尘过程的天气背景。浮尘天气造成21—24日喀什地区空气污染指数AQI指达500,属严重污染,首要污染物PM_(2.5)和PM_(10)在21日、22日达到峰值,分别为494、1 175μg/m~3。热力、动力条件以及近地面存在逆温层均不利于污染物的扩散。污染过程前后喀什市本站气压与PM_(10)、PM_(2.5)浓度均呈正相关,相关系数为0.762、0.507,均通过0.05显著性水平检验;气温与PM_(10)浓度呈负相关,与PM_(2.5)相关性不明显;相对湿度跟PM10和PM2.5呈正相关,表明气象因子在大气污染过程中对大气环境影响明显。     

邢台沙河市冬季大气污染特征与潜在源区分析

为了解邢台沙河市冬季大气污染特征,选取2017年12月至2018年2月沙河市区3个省控站点（司法局、市政府、宣传中心）的逐时监测数据,分析了沙河市主要污染物的时空分布特征和潜在源区。污染物浓度特征分析表明:整个冬季司法局、市政府和宣传中心站点的细颗粒物（PM2.5）平均浓度分别为118.0 μg/m3、121 μg/m3和135 μg/m3。在大气自然活动和人为污染排放的共同作用下,PM10、PM2.5、SO₂、NO₂和CO均有明显的日变化特征。整个冬季沙河市的ρ(PM2.5)/ρ(PM10)、ρ(SO₂)/ρ(NO₂)均值分别为0.57和1.05（ρ为各物质的浓度）。且随着污染加重,ρ(PM2.5)/ρ(PM10)、ρ(SO₂)/ρ(NO₂)均明显升高,表明燃煤贡献增加;污染物空间分布特征分析表明:位于3个站点东北处的玻璃企业产生的污染物可能对监测站点造成了一定影响。污染物空间差异分析表明,区域污染范围越大、强度越高,大气污染的空间差异性越小;潜在源分析表明:沙河市PM2.5的强潜在源区分布在其周边区域,随着PM2.5浓度增加,强潜在源区呈缩小趋势。沙河市东南部的本地源对PM2.5浓度有主要贡献,而此处正是玻璃企业的聚集地。     

Characteristics of Boundary Layer Structure during a Persistent Haze Event in the Central Liaoning City Cluster,Northeast China

The characteristics of boundary layer structure during a persistent regional haze event over the central Liaoning city cluster of Northeast China from 16 to 21 December 2016 were investigated based on the measurements of particulate matter (PM) concentration and the meteorological data within the atmospheric boundary layer (ABL). During the observational period, the maximum hourly mean PM2.5 and PM10 concentrations in Shenyang, Anshan, Fushun, and Benxi ranged from 276 to 355 μg m^–3 and from 378 to 442 μg m^–3, respectively, and the lowest hourly mean atmospheric visibility (VIS) in different cities ranged from 0.14 to 0.64 km. The central Liaoning city cluster was located in the front of a slowly moving high pressure and was mainly controlled by southerly winds. Wind speed (WS) within the ABL (< 2 km) decreased significantly and WS at 10-m height mostly remained below 2 m s^–1 during the hazy episodes, which was favorable for the accumulation of air pollutants. A potential temperature inversion layer existed throughout the entire ABL during the earlier hazy episode [from 0500 Local Time (LT) 18 December to 1100 LT 19 December], and then a potential temperature inversion layer developed with the bottom gradually decreased from 900 m to 300 m. Such a stable atmospheric stratification further weakened pollutant dispersion. The atmospheric boundary layer height (ABLH) estimated based on potential temperature profiles was mostly lower than 400 m and varied oppositely with PM_2.5 in Shenyang. In summary, weak winds due to calm synoptic conditions, strong thermal inversion layer, and shallow atmospheric boundary layer contributed to the formation and development of this haze event. The backward trajectory analysis revealed the sources of air masses and explained the different characteristics of the haze episodes in the four cities.     

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.     

Lower tropospheric transport over the Southern Ocean

Radon and particle concentrations obtained at Macquarie Island, halfway between Australia and Antarctica, and on Tasmania's north-west coast at Cape Grim during 1987 are examined. Four-day trajectories based on 12 hourly analyses over the Australian region are used to explore the transport of continental material across the Southern Ocean. This study suggests that at least 25% of the variance of radon concentration at Macquarie Island can be accounted for by transport from the Australian continent. Trajectories at intervals of one hour are used to demonstrate the agreement between episodes of trajectories passing over land and episodes of elevated radon and particle concentration. Wind roses of percentage probability of various levels of radon and particle concentration are compared with back trajectories for their accuracy in depicting episodes of continental air incursion.     

2013—2016年海口市空气质量特征及典型个例污染物来源分析

根据海南省环境科学研究院提供的海口站2013—2016年逐日空气污染数据,统计分析了海口市空气质量状况。综合应用高低空环流场、AQI指数结合MODIS卫星蓝光气溶胶厚度图,采用HYSPLIT轨迹聚类分析法、潜在源贡献因子法和浓度权重轨迹分析方法,重点分析了2013年12月海口空气污染的的主要输送路径,并探讨了首要污染物PM_2.5和O₃的潜在源区。结果表明：冬夏季风风向转换是海口发生空气污染的最主要气象原因,且首要污染物为PM_2.5,其次是PM₁₀和O₃;海口市空气质量达标率在97.1%,总体较好,AQI指数呈逐年下降趋势;值得关注的是,O₃呈逐年稳定上升趋势。大气污染物浓度受污染物排放和环流场共同影响,海口污染日对应的地面天气形势主要有3种类型,冷高压、变暖高压脊和台风外围下沉气流。此次污染过程中污染源是来自北方地区污染物长距离输送影响的结果。污染物个例分析中,首要污染物PM_2.5潜在源区主要集中在湖南和江西的交界处、广东沿海地区、广西北部、江西和福建的交界处以及浙江中部地区,这些潜在源区气团沿着轨迹1、2和4通过长距离输送到海口。海口O₃质量浓度贡献较大的区域主要集中在湖南和江西的交界处、粤西一带,主要沿着轨迹2将内陆地区的污染源输送到海口。     

输送对区域本底站痕量气体浓度的影响

利用HYSPLIT4轨迹模式计算了临安、上甸子和龙凤山区域大气本底站2005年7月-2007年6月的气块后向轨迹, 并通过聚类分析取得了各站点平均轨迹的空间分布和季节变化等结果。将各站点同期观测到的O₃, SO₂, NO_x和CO浓度通过滑动平均法去除季节变化, 取得其短期变化信号, 并将轨迹与这种短期变化信号对应, 比较真实地反映了排放源空间分布和轨迹移动特性对污染物浓度的影响。研究结果表明:移动高度高、速度快的气块不利于污染物积累, 对站点污染物起清除作用。但个别来自高空的轨迹会将富含O₃的气块输送到地面, 从而使站点O₃浓度升高。各站均有大约50%~60%的轨迹输送污染气块, 导致站点气体浓度升高。临安站的污染主要来自S-SW和N-SE扇区; 上甸子站的污染最主要来自SE-SW扇区, 其次来自N-SE和W-N扇区; 龙凤山的污染主要由来自S-WSW扇区。     

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。     

The fine and coarse particulate matter at four major Mediterranean cities: local and regional sources

Particulate air pollution is associated with adverse health effects to the population exposed. The aim of this paper is the identification of local and regional sources, affecting PM₁₀ and PM_2.5 levels in four large cities of southern Europe, namely: Lisbon, Madrid, Marseille, and Rome. Air pollution data from seven sampling sites of the European Union network were used. These stations were selected due to their ability of monitoring PM_2.5 concentrations and providing reliable series of data. Each station’s background was also taken into account. Pearson correlation coefficients and primal component analysis components were extracted separately for cold and warm periods in order to define the relationships among particle matters (PM_s) and gaseous pollutants (CO, NO₂, SO₂, and O₃) and evaluate the contributions of local sources. Possible seasonal variations of PM_2.5/PM₁₀ ratio daily values were also used as markers of PM sources, influencing particulate size distribution. Particle emissions were primarily attributed to traffic and secondarily to natural sources. Minimum daily values of PM_2.5/PM₁₀ ratio were observed during warm periods, particularly at suburban stations with rural background, due to dust resuspension and also due to the increase of biogenic coarse PM (pollen, dust, etc.). Hybrid Single-Particle Lagrangian Integrated Trajectory Model trajectory model was used in order to compute the 4-day backward trajectories of the air masses that affected the four cities which are under study during days with recorded PM₁₀ exceedances, within a 5-year period (2003–2007), at 300, 750, and 1,500 m above ground level (AGL). The trajectories were then divided to clusters with a K-means analysis. In all four cities, the influence of slow-moving air masses was associated with a large fraction of PM₁₀ exceedances and with high average and maximum daily mean PM₁₀ concentrations, principally at the 300 m AGL analysis. As far the issue of the increased PM₁₀ concentrations, the results were weaker in Marseille and particularly in Rome, probably due to their greater distance from Northwest Africa, in comparison to Madrid and Lisbon. Dust intrusions from the Sahara desert and transportation of Mediterranean/Atlantic sea spray, were characterized as primary regional sources of exogenous PM₁₀ in all four cities. Continental trajectories from the industrialized northern Italy affected PM₁₀ levels particularly in Marseille and Rome, due to their more eastern geographical position.     

泰山PM10及其中化学成分变化特征

为研究华北平原区域背景气溶胶成分及其变化特征,2010年6月至2011年7月在泰山顶采集了64个PM10滤膜样品,分析了样品的PM10及其中无机盐离子和有机碳（OC）、元素碳（EC）的质量浓度,并对各成分相关性等进行了分析。泰山PM10年均质量浓度约为68.4 mg/m³,其中无机盐离子约占总质量的64.8%,碳气溶胶约占17.4%。无机盐离子的质量浓度从春季逐渐增大,夏季达到峰值,秋季下降,冬季最小;OC质量浓度从春季至秋季逐渐增高,冬季最低,EC变化类似,但夏秋两季差别不大。二次有机碳（SOC）与OC的比值四季均在50%以上,年均值约为58.5%。通过后向轨迹聚类分析发现,在经过城市的较短轨迹以及南方较短混合轨迹的影响下,泰山PM10质量浓度较高,而西北长距离传输气团PM10浓度均较低。