2007年冬季沈阳典型大气污染源PM10排放模拟

选取沈阳市区9个典型的大气污染源冬季的PM10排放浓度资料,利用MM5耦合CALPUFF对2007年12月至2008年2月沈阳城市区域气象场和排放PM10浓度分布进行月平均数值模拟.结果表明:冬季沈阳地区受高压控制,北风较强,并经过增强、减弱的过程,多呈现对大气污染物扩散不利的天气形势.高空为偏西风且风速较大时,地面和...     

Terra和Aqua卫星MODIS 3 km AOD与北京PM_(2.5)对比分析

本文利用2014年全年北京市12个空气质量监测站的逐小时PM_(2.5)地面观测资料,以及Terra卫星和Aqua卫星的MODIS 3 km气溶胶光学厚度(AOD)产品,分析了地面PM_(2.5)和两颗卫星AOD的时空分布特征,并在时空匹配的基础上,建立了AOD与PM_(2.5)浓度之间的回归模型。结果表明:PM_(2.5)浓度在城区高、郊区低,最低值位于定陵站,城区站和郊区站的逐时PM_(2.5)浓度的日变化分别呈"双峰型"和"单峰型";两颗卫星AOD数值也均是城区高、郊区低,沿山区的边界有明显的AOD梯度,且城区上午Terra卫星的AOD高于下午Aqua卫星的AOD,而郊区上、下午的AOD基本相同;Aqua卫星AOD与PM_(2.5)的确定系数(R2)较Terra卫星AOD与PM_(2.5)的确定系数平均高0.11,且城区站点两颗卫星AOD与PM_(2.5)相关性均较郊区站点AOD与PM_(2.5)相关性偏高;综合来看,Aqua卫星的AOD与城区的PM_(2.5)相关系数最高,即Aqua卫星的AOD更适于监测和反演城区地面的PM_(2.5)。     

Influence of traffic emissions on the composition of atmospheric particles of different sizes – Part 1: concentrations and elemental characterization

Epidemiological studies initially considered the impact of total solid particles on human health, but according to the acquired knowledge about the worse effect of smaller particles, those studies turned to consider the impact of PM₁₀. However, for the last decade PM_2.5 began to be more important, once as they are smaller they can penetrate deeper in the lungs, being possible their trapping in alveoli and worse effects on human health. Therefore, more information on PM_2.5 should be provided namely concerning the levels and elemental composition. Considering the relevance of traffic on the emission of particles of small sizes, this work included the detailed characterization of PM₁₀ and PM_2.5, sampled at two sites directly influenced by traffic, as well as at two reference sites, aiming a further evaluation of the influence of PM₁₀ and PM_2.5 on public health. The specific objectives were to study the influence of traffic emission on PM₁₀ and PM_2.5 characteristics, considering concentration, size distribution and elemental composition. PM₁₀ and PM_2.5 samples were collected using low-volume samplers; the element analyses were performed by particle induced X-ray emission (PIXE). At the sites influenced by traffic emissions PM₁₀ and PM_2.5 concentrations were 7–9 and 6–7 times higher than at the background sites. The presence of 17 elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb) was determined in both PM fractions; particle metal contents were 3–44 and 3–27 times higher for PM₁₀ and PM_2.5, respectively, than at the backgrounds sites. The elements originated mostly from anthropogenic activities (S, K, V, Mn, Ni, Zn and Pb) were predominantly present in PM_2.5, while the elements mostly originated from crust (Mg, Al, Si and Ca) predominantly occurred in PM_2.5–10. The results also showed that in coastal areas sea salt spray is an important source of particles, influencing PM concentration and distributions (PM₁₀ increased by 46%, PM_2.5/PM₁₀ decreased by 26%), as well as PM compositions (Cl in PM₁₀ was 11 times higher).     

湖北2015年冬季PM2.5重污染过程的气象输送条件及日变化特征分析

PM_2.5污染仍然是湖北省冬季大气污染的首要污染类型,且具有明显区域传输特征,重污染过程的空气污染气象条件有别于华北地区,值得关注。采用WRF/Chem不同排放情景下的模拟结果,并结合观测分析,研究了2015年12月—2016年1月湖北省PM_2.5重污染过程的气象输送条件及日变化特征,从大尺度输送条件和局地边界层动力作用分析了外来污染物水平传输、悬浮聚集和向下传输的过程,并解释了该地区观测到的午后PM_2.5浓度特殊峰值的气象成因。结果表明,湖北重污染爆发以区域传输为主,地面观测PM_2.5极值对应10 m风速可达8—10 m/s,边界层0—1 km为较强偏北风输送,污染传输通量极值位于400 m高度附近,为重要传输通道,低空无明显逆温,重污染过程具有“非静稳”边界层气象特征。重污染形成的大尺度输送条件为,长江中下游及北部地区偏北风异常偏强,南部地区风速减缓,使污染物在中游平原堆积,鄂北边界风速越大,越有利污染输送增长。传输性污染主要来自偏北和东北方向的污染源输送,潜在源区贡献主要为途经偏北通道上的豫中、南阳盆地和关中地区,以及途经东北通道上的鲁、皖、苏等部分地区。PM_2.5浓度日变化双峰结构的天气成因不同,21—24时（北京时）峰值为静稳性污染,11—14时峰值为传输性污染。污染输送受大气边界层高度影响,日出前大气边界层高度较低,层结稳定并伴有上升运行,使得低空外来输送悬浮聚集在400 m高度附近;日出后随大气边界层高度升高,静稳层结被破坏,在干沉降作用下高浓度PM_2.5开始向下传输,并在午后地面形成峰值。      

四川盆地一次当地排放和沙尘输送双重影响的区域空气重污染过程研究

针对四川盆地大气污染及其成因的特殊性,本文使用四川盆地18个城市的大气污染监测和气象观测数据以及NCEP1°×1再分析资料,对2017年12月19日～2018年1月3日四川盆地由当地过量排放和外来沙尘输送双重影响的区域性大气污染过程进行分析。结果表明：2017年12月19～28日四川盆地环流场配置不利大气污染物扩散,垂直温度层结稳定,在当地污染源持续排放下污染物浓度缓慢上升,此阶段为静稳型大气污染。之后29日冷空气过程打破前期不利污染物扩散的环流场及垂直温度层结,导致气态污染物下降明显,但伴随冷空气活动的外来沙尘使PM10浓度迅速增大,使四川盆地部分城市出现沙尘型重污染;特别是广元地区受沙尘直接影响最严重,PM10浓度是原来的4.5倍;成都市虽没有通过沙尘天气的表观判断,但对颗粒物离子浓度和化学组分都有显著影响;因此,当时PM10和CO浓度24h比值变化受沙尘输送和天气条件共同影响,在不同时段和地区都存在明显差异,初步揭示出由静稳型大气污染向沙尘型污染转换阶段的内在变化特征,具有重要科学价值。     

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.     

基于空气质量模拟的江苏省大气污染物排放清单比较研究

大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单，即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单"，并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明，除二氧化硫（SO₂）以外，江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较，发现两套清单对SO₂、氮氧化物（NO_x）、臭氧（O₃）和细颗粒物（PM_2.5）的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近，其中江苏省清单模拟的PM_2.5和O₃在长三角多数地区略低于长三角清单的模拟结果（1月O₃除外）.江苏省清单与长三角清单均能够用于空气质量模式模拟，可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.     

2020年新冠肺炎疫情管控期江苏省大气污染物浓度变化特征

利用江苏省大气环境监测站点的大气污染物监测数据,分析了2020年初新冠肺炎疫情管控期间(2—3月)主要大气污染物浓度的变化特征。结果显示,相比于2019、2020年疫情管控期间PM_2.5、PM₁₀、NO₂、SO₂、CO浓度的全省平均降幅分别为37.5%、36.9%、31.9%、28.2%和21.2%。严格管控期的2月和生产恢复期的3月,江苏省十三市PM_2.5、PM₁₀浓度同比降幅大致相当,呈现出较好的时间连续性和空间均匀性。但各市臭氧浓度同比变化呈现出较大的时空差异。空间上,沿江以南城市南京、无锡、常州、苏州和镇江五市臭氧浓度明显上升,而其他城市臭氧浓度以下降为主;时间上,2月南京等九市臭氧浓度上升,3月徐州等八市臭氧浓度持平或者下降。假设未发生新冠肺炎疫情以及未采取为阻断疫情蔓延而实施的种种举措,在仅考虑近年来大气污染防治政策持续实施的情况下,与预期降幅相比,疫情管控对NO₂实况浓度降幅的影响最大,其次是PM_2.5     

卫星气溶胶光学厚度资料同化对灰霾预报改进个例研究

面对日益严峻的大气污染形势,针对卫星气溶胶光学厚度（AOD）资料在灰霾数值预报领域的合理有效利用问题,使用WRF-Chem（WRF coupled with Chemistry）大气化学模式以及GSI（Gridpoint Statistical Interpolation）三维变分同化系统,利用MODIS和FY-3A/MERSI AOD资料,对一次灰霾天气过程进行了同化预报试验。试验结果显示,同化卫星AOD资料有效改善了模式初始场,MODIS和MERSI同化试验分别在AOD分析场的中心强度和空间分布各具优势,且对PM_2.5和PM₁₀的后续预报改进明显;从统计分析上看,同化试验的预报效果整体上好于控制试验,同化试验中PM_2.5和PM₁₀预报值的平均值、中值、平均偏差、均方根误差等指标均明显优于控制试验,且MODIS和MERSI同化试验分别在PM_2.5和PM₁₀预报统计结果中体现出了优势;卫星AOD资料同化能明显降低污染事件的空报率和漏报率,提高预报的TS评分和ETS评分。不同卫星AOD资料的差异对分析场中AOD的分布和强度产生了相应影响,进而影响了模式的灰霾预报效果;本次试验中,MODIS和MERSI AOD同化试验分别在PM_2.5和PM₁₀预报的评分上表现更佳。结果表明,卫星AOD资料同化对数值预报产生了积极的效果。      

基于京津冀高密度地面观测网络的大气污染物浓度地面观测代表性误差估计

地面观测提供空间点的浓度信息,三维化学模式提供网格面的浓度信息,两者在进行对比验证或同化融合时会因为空间尺度不匹配引入误差,即观测代表性误差。本研究将大气污染地面国控监测站与区县监测站结合起来,获得了京津冀地区高密度地面观测数据,利用该数据首次对京津冀地区6项常规大气污染物（PM_2.5、PM₁₀、SO₂、NO₂、CO和O₃）的地面观测代表性误差进行了客观估计,并与Elbern et al.（2007）方法估计的代表性误差进行了对比。结果发现:两种方法对京津冀地区NO₂地面观测代表性误差估计非常接近,但Elbern et al.（2007）方法显著低估了SO₂、CO和O₃地面观测的代表性误差。在此基础上,我们对Elbern et al.（2007）方法及其误差特征参数进行了本地化修正,并增加了PM_2.5和PM₁₀的代表性误差特征参数,建立了京津冀大气污染地面观测代表性误差的客观估计方法。     

西安市PM2.5城乡差异及与城市热岛的关联研究

依据一种基于建筑用地比例和土地利用信息熵的城乡站点划分方法,将西安市环境与气象站点划分为城区、郊区和两类乡村站,讨论其PM_2.5的城乡分布特征及与城市热岛效应强度(Urban Heat Island Intensity,UHII)间的相关关系。结果表明,不同季节西安市呈现不同的PM_2.5城乡分布特征和日变化特征,两类乡村站点PM_2.5差异明显且下风向乡村站点(乡村D)对应的UHII_D对城区和乡村的影响程度大于上风向乡村站点(乡村U)对应的UHII_U。在城区较多本地排放的影响下,乡村PM_2.5浓度与 UHII_U(或UHII_D)相关系数均大于城区。随着UHII_D的增加,城乡PM_2.5相对浓度差值(RUPII_D)整体呈下降趋势且UHII_D与RUPII_D在春夏秋季显著负相关。UHII_D增大,城区近地面PM_2.5的水平扩散能力减弱,但PM_2.5的垂直扩散能力较乡村更强,从而UHII_D通过影响PM_2.5的传输扩散特征,进一步影响西安市RUPII_D。     

Extreme Particulate Levels at a Western Pacific Coastal City: The Influence of Meteorological Factors and the Contribution of Long-Range Transport

The 4-year data sets (1998–2001) of PM₁₀ and other gaseous pollutants at four rural and urban monitoring sites provided by Environmental Protection Department of Hong Kong have been analyzed for days of extremely high and low PM₁₀ levels. The annual means of PM₁₀ concentrations are between 37 and 57 μg/m³. The level of high PM₁₀ concentration is defined from the comparison of local and international standards. Episode days are mainly controlled by different meteorological conditions: the continental outflow, the land-sea breeze/weak synoptic forcings and the approaching tropical cyclones. Integrated approaches have been used to distinguish between the predominantly “territory wide” and “long-range transport” (LRT) episode days. Case studies of these types of episodes are presented and the number of episode days per year for each type has been estimated. It is found that the LRT contributions are significant and account for ∼66% of the PM₁₀ episode days. Very high correlations between CO and PM₁₀ concentrations, and between SO₂ and PM₁₀ concentrations, can be found during the “territory wide” episode days which implies the important contributions of fossil fuel combustion to the PM₁₀ episodes. The number of “low level” PM₁₀ days per year has decreased by a factor near 3 from 1998 to 2001. Precipitation scavenging is the major process causing low levels of PM₁₀, irrespective of the associated weather systems. The regional annual background level is ∼9 μg/m³. With the exception of seasalt components, the average elemental concentrations of major inorganic species are similar for all of the sites during LRT events and constitute representative compositions of PM₁₀ during such events.     

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.     

Particle composition and size distributions in and around a deep-pit swine operation,Ames, IA

The contribution of emissions from agricultural facilities is rapidly becoming a major concern for local and regional air quality. Characterization of particle properties such as physical size distribution and chemical composition can be valuable in understanding the processes contributing to emissions and ultimate fate of particulate matter from agricultural facilities. A measurement campaign was conducted at an Iowa, deep-pit, three-barn swine finishing facility to characterize near-source ambient particulate matter. Size-specific mass concentrations were determined using minivol samplers, with additional size distribution information obtain using optical particle counters. Particulate composition was determined via ion chromatographic analysis of the collected filters. A thermal-CO₂ elemental/organic carbon analyzer measured particulate carbon. The chemical composition and size distribution of sub-micron particles were determined via real-time aerosol mass spectrometry. Primary particulate was not found to be a major emission from the examined facility, with filter-based impactor samples showing average near-source increases (~15–50 m) in ambient PM₁₀ of 5.8 ± 2.9 μg m⁻³ above background levels. PM_2.5 also showed contribution attributable to the facility (1.7 ± 1.1 μg m⁻³). Optical particle counter analysis of the numerical size distributions showed bimodal distributions for both the upwind and downwind conditions, with maximums around 2.5 μm and below the minimum quantified diameter of 0.3 μm. The distributions showed increased numbers of coarse particles (PM₁₀) during periods when wind transport came from the barns, but the differences were not statistically significant at the 95% confidence level. The PM₁₀ aerosols showed statistically increased concentrations of sulfate, nitrate, ammonium, calcium, organic carbon, and elemental carbon when the samplers were downwind from the pig barns. Organic carbon was the major constituent of the barn-impacted particulate matter in both sub-micron (54%) and coarse size (20%) ranges. The AMS PM₁ chemical speciation showed similar species increases, with the exception of and Ca⁺², the latter not quantified by the AMS.     

Spatiotemporal analysis of particulate matter, sulfur dioxide and carbon monoxide concentrations over the city of Rio de Janeiro, Brazil

Time series of pollutants and weather variables measured at four sites in the city of Rio de Janeiro, Brazil, between 2002 and 2004, were used to characterize temporal and spatial relationships of air pollution. Concentrations of particulate matter (PM₁₀), sulfur dioxide (SO₂) and carbon monoxide (CO) were compared to national and international standards. The annual median concentration of PM₁₀ was higher than the standard set by the World Health Organization (WHO) on all sites and the 24?h means exceeded the standards on several occasions on two sites. SO₂ and CO did not exceed the limits, but the daily maximum of CO in one of the stations was 27% higher on weekends compared to weekdays, due to increased activity in a nearby Convention Center. Air temperature and vapor pressure deficit have both presented the highest correlations with pollutant??s concentrations. The concentrations of SO₂ and CO were not correlated between sites, suggesting that local sources are more important to those pollutants compared to PM₁₀. The time series of pollutants and air temperature were decomposed in time and frequency by wavelet analysis. The results revealed that the common variability of air temperature and PM₁₀ is dominated by temporal scales of 1?C8?days, time scales that are associated with the passage of weather events, such as cold fronts.     

Estimation of transboundary transport contribution to the air pollution in the far east region using the chemistry transport model

The CHIMERE mesoscale chemistry transport model is used for the quantitative assessment of the contribution of transboundary transport of anthropogenic admixtures from China to the surface concentrations of major suspended pollutants, aerosol PM₁₀, ozone O₃, and nitrogen oxides NO_x in the Far Eastern region. Analyzed in detail are the time series of concentration of mentioned substances computed with the model taking account and not taking account of anthropogenic emissions in China. It is revealed that the transboundary transport of anthropogenic pollutants can cause the recurring episodes of manyfold increase in the concentration of PM₁₀ in the south of Khabarovsk region, as well as more rare variations of O₃ and NO_x concentration. The trajectory and synoptic analysis demonstrated that the episodes of the increase in the concentration of PM₁₀ and O₃ in the south of the region mainly depend on the carryover of air masses from northeastern China in the front part of continental cyclones.     

Relative influence of air pollutants and weather conditions on solar radiation – Part 1: Relationship of air pollutants with weather conditions

Summary Air pollution measurements from January 1999 to December 2003 were studied in 14 sites covering most of Egypt, with the aim of understanding the governing processes pollutants phase interaction. The nature of the contributing sources has been investigated, and some attempts have been made to indicate the role played by neighboring regions in determining the air quality at these sites. The seasonal variability of particulate matter (PM₁₀) and some gaseous pollutants (e.g., SO₂, NO₂, CO and O₃) were analyzed. Their relationships with meteorology were also examined. The results reveal that levels of major air pollutants were not significantly different at the rural and background sites during any season. On contrary the high atmospheric loading for PM₁₀, CO and SO₂ was frequently observed in winter at the urban sites. As expected, the prevailing winds were found to have an influence not only on air pollutants but also on the correlation between them.     

2015—2019年防城港市空气污染气象条件综合分析

对防城港市影响最大的首要空气污染物为PM_2.5和O₃,空气污染日主要集中在秋冬季。空气污染按500 hPa环流形势可分为西北气流型、偏西气流型及西南气流型;按地面气压场可分为冷高压脊型、均压型、高压后部低压前部型。在无境外输入的情况下,PM_2.5产生在风速小、气温较低、能见度小、湿度较大并且无降雨或降雨不明显的天气环境里,而O₃产生在高温、低湿、日照充足、风速较大和能见度好的天气环境里。在垂直运动方面,中低层的下沉气流利于空气污染物累积。在温度层结分布方面,700~850 hPa的低层存在的逆温层对PM_2.5浓度增加非常重要,近地面的逆温层对PM_2.5浓度增加的作用要比低层弱,而近地面的逆温层对O₃浓度的增加非常重要,但是低层的逆温却不重要。     

Influence of traffic emissions on the composition of atmospheric particles of different sizes—Part 2: SEM–EDS characterization

In urban areas traffic is the major contributor to atmospheric particulate matter and exposure to these particles currently represents a serious risk to human health. The attention has been recently focused more on the particles of smaller sizes (PM_2.5) which penetrate deeper in respiratory system causing severe health effects. Therefore, more information on PM_2.5 should be provided, namely concerning morphological and chemical characterization. Aiming further evaluation of the impact of traffic emissions on public health, this work evaluated the influence of traffic on the chemical and morphological characteristics of PM₁₀ and PM_2.5, collected at one site influenced by traffic emissions and at one reference site. Chemical and morphological characteristics of 1,000 individual particles were determined by scanning electron microscopy combined with energy dispersive spectrometer (SEM–EDS). Cluster analysis (CA) was used to identify different types of particles that occurred in PM, aiming the identification of the respective emission sources. Traffic PM_2.5 were dominated by particles composed of Fe oxides and alloys (67%) which were related to traffic emissions (this percentage was 3.7 times higher than at the background site); in PM_2.5–10 the abundance of Fe oxides and alloys were 20% and 0% for the traffic and background sites, respectively. Background PM_2.5 were mainly constituted by aluminum silicates (63%) related to natural sources (this percentage was 2.5 times higher than at the traffic site); the abundances of aluminum silicates in PM_2.5–10 were 74% and 73% for traffic and background sites, respectively. It was concluded that traffic emissions were mainly present in PM_2.5 (the percentage of particles associated to these emissions was 3.4 times higher than in PM_2.5–10), while coarse particles were dominated by material of natural origin (the percentage of particles associated was 1.2 and 3.0 times higher than in PM_2.5 for traffic and background sites, respectively). Previous results obtained by proton induced X-ray emission (PIXE) were consistent with SEM–EDS analysis that showed to be very useful to complement elemental analysis of different PM_2.5 and PM_2.5–10.     

上海市PM_(10)浓度四季遥感模型研究

通过分析2001—2012年上海市PM_(10)浓度(由API(Air Pollution Index)转化得到)的变化规律,构建了上海市PM_(10)浓度的遥感反演模型。结果表明:1)上海市PM_(10)浓度存在季节性变化,应分别建立遥感反演模型。2)分析MODIS气溶胶光学厚度(Aerosol Optical Depth,AOD)产品与PM_(10)浓度之间的相关性发现,AOD须经过垂直和湿度订正才可与PM_(10)建立较好的关系。3)结合垂直和湿度订正分别建立的上海市PM_(10)浓度春夏秋冬四季的遥感反演模型均通过了拟合度检验,其中春季模型采用指数函数、夏季和秋季模型采用二次多项式函数、冬季采用幂函数、全年采用二次多项式函数,利用此四季模型反演上海市PM_(10)浓度具有较高的可信度。