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.     

Geochemistry of regional background aerosols in the Western Mediterranean

The chemical composition of regional background aerosols, and the time variability and sources in the Western Mediterranean are interpreted in this study. To this end 2002–2007 PM speciation data from an European Supersite for Atmospheric Aerosol Research (Montseny, MSY, located 40 km NNE of Barcelona in NE Spain) were evaluated, with these data being considered representative of regional background aerosols in the Western Mediterranean Basin. The mean PM₁₀, PM_2.5 and PM₁ levels at MSY during 2002–2007 were 16, 14 and 11 µg/m³, respectively. After compiling data on regional background PM speciation from Europe to compare our data, it is evidenced that the Western Mediterranean aerosol is characterised by higher concentrations of crustal material but lower levels of OM + EC and ammonium nitrate than at central European sites. Relatively high PM_2.5 concentrations due to the transport of anthropogenic aerosols (mostly carbonaceous and sulphate) from populated coastal areas were recorded, especially during winter anticyclonic episodes and summer midday PM highs (the latter associated with the transport of the breeze and the expansion of the mixing layer). Source apportionment analyses indicated that the major contributors to PM_2.5 and PM₁₀ were secondary sulphate, secondary nitrate and crustal material, whereas the higher load of the anthropogenic component in PM_2.5 reflects the influence of regional (traffic and industrial) emissions. Levels of mineral, sulphate, sea spray and carbonaceous aerosols were higher in summer, whereas nitrate levels and Cl/Na were higher in winter. A considerably high OC/EC ratio (14 in summer, 10 in winter) was detected, which could be due to a combination of high biogenic emissions of secondary organic aerosol, SOA precursors, ozone levels and insolation, and intensive recirculation of aged air masses. Compared with more locally derived crustal geological dusts, African dust intrusions introduce relatively quartz-poor but clay mineral-rich silicate PM, with more kaolinitic clays from central North Africa in summer, and more smectitic clays from NW Africa in spring.     

Case study of PM pollution in playgrounds in Istanbul

In a world where at least 50% of the population is living in urban environments, air pollution and specifically particulate matter (PM) have become one of the most critical issues for human health. Children are more susceptible than adults to air pollution and its adverse effects because they inhale and retain larger amounts of air pollutants per unit of body weight. In this study, PM pollution, particularly PM₁₀ and PM_2.5, at selected playgrounds were investigated in Istanbul city. Istanbul is a megacity of over 15 million inhabitants, and on-road traffic is increasing rapidly (over 3 million vehicles on the road). To estimate the effect of traffic emissions on children, the location of the playgrounds were selected according to traffic density. Measurements were carried out at five different playgrounds throughout the city in 2009. Field results show that the values of PM₁₀ and PM_2.5 have reached critical limits at the playgrounds close to the main roads, especially at P-1. Thus, we focused on this location and investigated a source other than traffic emissions. One of the episode days has been observed on 5–7 March 2009. Evaluations of meteorological events are very important to determine air pollution sources and their long-range transport. Therefore, the Weather Research and Forecasting model (WRF) was used to simulate and forecast meteorological parameters and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) applied to investigate long-range transport. According to the WRF model outputs, there was a low-pressure system over Geneva gulf on the 500-hPa level, and its core had been located over Britain on 5 March 2009 00UTC. The system had been sweeping dust from the Sahara Desert and carrying the air particles over Istanbul. Similarly, backward HYSPLIT analysis showed that air particles had moved through Istanbul from Northern Africa.     

Investigating the Transport Mechanism of PM2.5 Pollution during January 2014 in Wuhan,Central China

Severe haze pollution that occurred in January 2014 in Wuhan was investigated. The factors leading to Wuhan’s PM_2.5 pollution and the characteristics and formation mechanism were found to be significantly different from other megacities, like Beijing. Both the growth rates and decline rates of PM_2.5 concentrations in Wuhan were lower than those in Beijing, but the monthly PM_2.5 value was approximately twice that in Beijing. Furthermore, the sharp increases of PM_2.5 concentrations were often accompanied by strong winds. A high-precision modeling system with an online source-tagged method was established to explore the formation mechanism of five haze episodes. The long-range transport of the polluted air masses from the North China Plain (NCP) was the main factor leading to the sharp increases of PM_2.5 concentrations in Wuhan, which contributed 53.4% of the monthly PM_2.5 concentrations and 38.5% of polluted days. Furthermore, the change in meteorological conditions such as weakened winds and stable weather conditions led to the accumulation of air pollutants in Wuhan after the long-range transport. The contribution from Wuhan and surrounding cities to the PM_2.5 concentrations was determined to be 67.4% during this period. Under the complex regional transport of pollutants from surrounding cities, the NCP, East China, and South China, the five episodes resulted in 30 haze days in Wuhan. The findings reveal important roles played by transregional and intercity transport in haze formation in Wuhan.     

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.     

PM2.5 co-benefits of climate change legislation part 1: California’s AB 32

The Scoping Plan for compliance with California Assembly Bill 32 (Global Warming Solutions Act of 2006; AB 32) proposes a substantial reduction in 2020 greenhouse gas (GHG) emissions from all economic sectors through energy efficiency, renewable energy, and other technological measures. Most of the AB 32 Scoping Plan measures will simultaneously reduce emissions of traditional criteria pollutants along with GHGs leading to a co-benefit of improved air quality in California. The present study quantifies the airborne particulate matter (PM_2.5) co-benefits of AB 32 by comparing future air quality under a Business as Usual (BAU) scenario (without AB 32) to AB 32 implementation by sector. AB 32 measures were divided into five levels defined by sector as follows: 1) industrial sources, 2) electric utility and natural gas sources, 3) agricultural sources, 4) on-road mobile sources and 5) other mobile sources. Air quality throughout California was simulated using the UCD source-oriented air quality model during 12 days of severe air pollution and over 108 days of typical meteorology representing an annual average period in the year 2030 (10 years after the AB 32 adoption deadline). The net effect of all AB 32 measures reduced statewide primary PM and NO_x emissions by ~1 % and ~15 %, respectively. Air quality simulations predict that these emissions reductions lower population-weighted PM_2.5 concentrations by ~6 % for California. The South Coast Air Basin (SoCAB) experienced the greatest reductions in PM_2.5 concentrations due to the AB 32 transportation measures while the San Joaquin Valley (SJV) experiences the smallest reductions or even slight increases in PM_2.5 concentrations due to the AB 32 measures that called for increased use of dairy biogas for electricity generation. The ~6 % reduction in PM_2.5 exposure associated with AB 32 predicted in the current study reduced air pollution mortality in California by 6.2 %, avoiding 880 (560–1100) premature deaths per year for the conditions in 2030. The monetary benefit from this avoided mortality was estimated at $5.4B/yr with a weighted average benefit per tonne of $35 k/tonne ($23 k/tonne–$45 k/tonne) of PM, NO_x, SO_x, and NH₃ emissions reduction.     

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北大核心

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)、PM_(10)、NO_(2)、SO_(2)、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)、PM_(10)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NO_(2)实况浓度降幅的影响最大,其次是PM_(2.5)和PM_(10)。     

Regional model for formation,dynamics and Long-range transport of atmospheric aerosol: Study of atmospheric aerosol properties in Europe

This paper provides performance evaluation of the EMEP (Cooperative Programme for the Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) model, formulated in [1], and presents model calculation results. A satisfactory agreement is found between calculated and observed PM₁₀ and PM_2.5 concentrations (i.e., particulate matter with diameters smaller than 10 and 2.5 μm) and their chemical composition for different parts of Europe for the years 2001–2004. The model manages to reproduce observed regional gradients of background PM₁₀ and PM_2.5, with spatial correlations being 0.70 and 0.80, respectively, while the temporal correlation coefficients between modeled and measured daily PM vary mostly between 0.4 and 0.8 at EMEP sites. The agreement between calculated and observed aerosol number concentrations is worse than for mass concentrations. Model calculated PM₁₀ and PM_2.5 concentrations and chemical composition in Europe for the year 2004 are presented, as well as their interannual variations in the period 2000–2004. Further, contributions of different sources to PM₁₀ and PM_2.5 are estimated. Model results show that in 2004, background PM₁₀ and PM_2.5 exceeded EU critical levels and WHO recommended guidelines in a number of European regions. They also show that the transboundary transport contributes considerably to PM pollution in the European countries.     

Variations of levels and composition of PM10 and PM2.5 at an insular site in the Western Mediterranean

The insular suburban site of Castillo de Bellver was selected for the study of the variability of PM levels and composition in the Western Mediterranean Basin (WMB).Mean annual (in 2004) PM₁₀ and PM_2.5 levels at this site were 29 and 20 µg/m³, respectively. These levels may be regarded as relatively low when compared with other suburban insular locations in the Eastern Mediterranean Basin (EMB), but they are higher than those recorded at most of the European suburban sites, especially in Northern and Western Europe. Seasonal variability of PM levels at this site is governed by meteorology rather than local emissions, whereas the daily cycles are clearly defined by the anthropogenic emissions, mainly coming from the urban area of Palma de Mallorca and the harbour area of the same city.Concerning the aerosol composition at this site, the main PM constituent is the mineral matter (29% in PM₁₀ and 16 % in PM_2.5), more than 50% (in PM₁₀) being attributable to African dust. The amount of secondary inorganic aerosols is also very high (27% in PM₁₀ and 34% in PM_2.5), with the predominance of fine ammonium sulphate, and in a less proportion fine ammonium nitrate (in winter) and coarse Ca and Na nitrate (with higher importance in summer). The carbonaceous particles, dominantly fine, account for 17% of PM₁₀ and 25% of PM_2.5. The elemental carbon/organic carbon (EC/OC) ratio reached a mean value of 0.17, similar to those observed at regional background sites in the WMB coast of Spain. The sea spray aerosols (mainly coarse) represented around 10% of PM₁₀, and only 4% in PM_2.5. Finally, the unaccounted fraction increased from 15% to 20% in PM_2.5, being mostly attributed to water.The concentrations of trace elements in PM₁₀ and PM_2.5 were usually in the range to those observed in regional background sites in the Iberian Peninsula, with the exception of the typical tracers of road traffic such as Cu, Sb, Zn, Sn and Ba, which presented concentrations in the range of urban sites of Iberia. Other elements such as Cr, Zr, Hf and Co have been identified as the main tracers of the harbour contributions.     

武汉市冬季灰霾期PM2.5中水溶性无机离子的特征

2018年1月,利用颗粒物采样器采集武汉市大气PM_2.5样品并进行水溶性无机离子（F^-、Cl^-、NO₃^-、SO₄^2-、Na⁺、NH₄⁺、K⁺、Mg²⁺、Ca²⁺）的分析.结果表明,NO₃^-、SO₄^2-、NH₄⁺是PM_2.5中最主要的3种水溶性无机离子,除Mg²⁺与Ca²⁺外,PM_2.5与WSⅡs （水溶性无机离子）之间的相关性显著,且移动源贡献占主导地位.阴阳离子平衡表明武汉市冬季灰霾期PM_2.5呈中性或弱酸性.通过混合单粒子拉格朗日综合轨迹模式模拟并采用分层聚类得出了4种主要的后向气流轨迹及相应的PM_2.5和水溶性离子浓度,结果表明区域传输对此次灰霾期影响较大.     

Influences of meteorological conditions on interannual variations of particulate matter pollution during winter in the Beijing–Tianjin–Hebei area

To investigate the interannual variations of particulate matter (PM) pollution in winter, this paper examines the pollution characteristics of PM with aerodynamic diameters of less than 2.5 and 10 μm (i.e., PM_2.5 and PM₁₀), and their relationship to meteorological conditions over the Beijing municipality, Tianjin municipality, and Hebei Province—an area called Jing–Jin–Ji (JJJ, hereinafter)—in December 2013–16. The meteorological conditions during this period are also analyzed. The regional average concentrations of PM_2.5 (PM₁₀) over the JJJ area during this period were 148.6 (236.4), 100.1 (166.4), 140.5 (204.5), and 141.7 (203.1) μg m^–3, respectively. The high occurrence frequencies of cold air outbreaks, a strong Siberian high, high wind speeds and boundary layer height, and low temperature and relative humidity, were direct meteorological causes of the low PM concentration in December 2014. A combined analysis of PM pollution and meteorological conditions implied that control measures have resulted in an effective improvement in air quality. Using the same emissions inventory in December 2013–16, a modeling analysis showed emissions of PM_2.5 to decrease by 12.7%, 8.6%, and 8.3% in December 2014, 2015, and 2016, respectively, each compared with the previous year, over the JJJ area.     

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).     

武汉市大气污染源排放清单及分布特征研究

以武汉市为研究区域,基于实地调查获得典型行业污染源活动水平,以大气污染物排放清单编制技术指南为参考,利用排放因子法建立2014年武汉市大气污染源排放清单,并结合经纬度、人口密度分布、土地利用类型、道路长度等数据将排放清单进行了3 km×3 km网格化处理.结果表明,2014年武汉市SO₂、NO_x、PM₁₀、PM_2.5、CO、BC、OC、VOCs和NH₃排放量分别为10.3、17.0、16.3、7.1、63.1、0.6、0.4、19.8和1.6万t.固定燃烧源为SO₂排放的主要来源,其贡献率约64%;移动源为NO_x的主要来源,其贡献率约51%;颗粒物排放主要来源于扬尘源和工艺过程源;CO和VOCs主要来源于工艺过程源,BC和OC排放均以移动源和生物质燃烧源为主,NH₃排放主要来自农业源.污染物排放主要集中在青山区至新洲区一带.     

Chemical characterization and multivariate analysis of atmospheric PM<Subscript>2.5</Subscript> particles

The new European Council Directive (PE-CONS 3696/07) frames the inhalable (PM₁₀) and fine particles (PM_2.5) on priority to chemically characterize these fractions in order to understand their possible relation with health effects. Considering this, PM_2.5 was collected during four different seasons to evaluate the relative abundance of bulk elements (Cl, S, Si, Al, Br, Cu, Fe, Ti, Ca, K, Pb, Zn, Ni, Mn, Cr and V) and water soluble ions (F⁻, Cl⁻, NO₂ ⁻, NO₃ ⁻, SO₄ ²⁻, Na⁺, NH₄ ⁺, Ca²⁺ and Mg²⁺) over Menen, a Belgian city near the French border. The air quality over Menen is influenced by industrialized regions on both sides of the border. The most abundant ionic species were NO₃ ⁻, SO₄ ²⁻ and NH₄ ⁺, and they showed distinct seasonal variation. The elevated levels of NO₃ ⁻ during spring and summer were found to be related to the larger availability of the NO_x precursor. The various elemental species analyzed were distinguished into crustal and anthropogenic source categories. The dominating elements were S and Cl in the PM_2.5 particles. The anthropogenic fraction (e.g. Zn, Pb, and Cu) shows a more scattered abundance. Furthermore, the ions and elemental data were also processed using principal component analysis and cluster analysis to identify their sources and chemistry. These approach identifies anthropogenic (traffic and industrial) emissions as a major source for fine particles. The variations in the natural/anthropogenic fractions of PM_2.5 were also found to be a function of meteorological conditions as well as of long-range transport of air masses from the industrialized regions of the continent. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Climate Change driven evolution of hazards to Europe’s transport infrastructure throughout the twenty-first century

Air circulation due to the urban heat island (UHI) effect can influence the dispersion of air pollutants in a metropolis. This study focusses on the influence of the UHI effect on particulate matter (PM; including PM_2.5 and PM_2.5–10) between May and September 2010–2012 in the Taipei basin. Meteorological and PM data were obtained from the sites, owned by the governmental authorities. The analysis was carried out using t test, relative indices (RIs), Pearson product–moment correlation and stepwise regression. The results show that the RI values for PM were the highest at moderate UHI intensity (MUI; 2 °C ≤ UHI < 4 °C) rather than at strong UHI intensity (SUI; 4 °C ≤ UHI) during the peak time for anthropogenic emissions (20:00 LST). Neither the accumulation of PM nor the surface convergence occurred in the hot centre, as shown by the case study. At MUI, more than 89 % of the synoptic weather patterns showed that the weather was clear and hot or that the atmosphere was stable. The variation in PM was associated with horizontal and vertical air dispersion. Poor horizontal air dispersion, with subsidence, caused an increase in PM at MUI. However, the updraft motion diluted the PM at SUI. The stepwise regression models show that the cloud index and surface air pressure determined the variation in PM_2.5–10, while cloud index, wind speed and mixing height influenced the variation in PM_2.5. In conclusion, a direct relationship between UHI effect and PM was not obvious.     

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.     

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。     

Investigating the Changes in Air Pollutant Emissions over the Beijing-Tianjin-Hebei Region in February from 2014 to 2019 through an Inverse Emission Method

In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei(BTH)region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ens...     

关中5市环境空气质量特征与成因分析

基于国家生态环境部发布的环境空气质量监测数据等资料,采取调查研究与量化分析相结合的方法,对关中地区西安、渭南、咸阳、铜川、宝鸡5市空气质量的总体特征和空间差异进行研究.结果表明：颗粒污染物普遍严重超标,其中PM_2.5和PM₁₀分别超标91%和77%;空气污染具有明显的季节性,冬季的首要污染物是PM_2.5和PM₁₀,夏季的主要污染物是O₃;关中空气污染受地形、气象条件和工业排放、采暖、施工、道路扬尘、汽车尾气等人类活动综合影响,大气污染具有相似性,同时表现出一定的差异性.     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 mass (21.5 μg m^− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM_2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.