Analysis of chemical characteristics of PM<Subscript>2.5</Subscript> in Beijing over a 1-year period

Beijing is one of the largest and most densely populated cities in China. PM_2.5 (fine particulates with aerodynamic diameters less than 2.5 μm) pollution has been a serious problem in Beijing in recent years. To study the temporal and spatial variations in the chemical components of PM_2.5 and to discuss the formation mechanisms of secondary particles, SO₂, NO₂, PM_2.5, and chemical components of PM_2.5 were measured at four sites in Beijing, Dingling (DL), Chegongzhuang (CG), Fangshan (FS), and Yufa (YF), over four seasons from 2012 to 2013. Fifteen chemical components, including organic carbon (OC), elemental carbon (EC), K⁺, NH₄ ⁺, NO₃ ^?, SO₄ ^2?, Cl^?, Al, Ca, Fe, Mg, Na, Pb, Si, and Zn, were selected for analysis. Overall, OC, SO₄ ^2?, NO₃ ^?, and NH₄ ⁺ were dominant among 15 components, the annual average concentrations of which were 22.62 ± 21.86, 19.39 ± 21.06, 18.89 ± 19.82, and 13.20 ± 12.80 μg·m^?3, respectively. Compared with previous studies, the concentrations of NH₄ ⁺ were significantly higher in this study. In winter, the average concentrations of OC and EC were, respectively, 3 and 2.5 times higher than in summer, a result of coal combustion during winter. The average OC/EC ratios over the four sites were 4.9, 7.0, 8.1, and 8.4 in spring, summer, autumn, and winter, respectively. The annual average [NO₃ ^?]/[SO₄ ^2?] ratios in DL, CG, FS, and YF were 1.01, 1.25, 1.08, and 1.12, respectively, which were significantly higher than previous studies in Beijing, indicating that the contribution ratio of mobile source increased in recent years in Beijing. Analysis of correlations between temperature and relative humidity and between SOR ([SO₄ ^2?]/([SO₄ ^2?] + [SO₂])) and NOR ([NO₃ ^?]/([NO₃ ^?] + [NO₂])) indicated that gas-phase oxidation reactions were the major formation mechanism of SO₄ ^2? in spring and summer in urban Beijing, whereas slow gas-phase oxidation reactions and heterogeneous reactions both occurred in autumn and winter. NO₃ ^? was mainly formed through year-round heterogeneous reactions in urban Beijing.     

Chemical characteristics of haze during summer and winter in Guangzhou

Airborne particles were collected with a 10-stage MOUDI and a PM₁₀ sampler in Guangzhou, China, during both haze and normal days in the summer of 2002 and 2003, and winter 2002. The characteristics of PAHs, organic carbon, elemental carbon and water-soluble inorganic ions were studied under four periods (summer normal, summer haze, winter normal and winter haze). In this study, secondary pollutants (OC, SO₄²⁻, NO₃⁻ and NH₄⁺) were the major chemical components and appeared to show a remarkably rapid increase from normal to haze days. The particle mass size distributions were bimodal and dominated by fine particles in haze days. A significantly higher OC/EC ratio was found in haze days (3.2–4.7) compared to normal days (1.8–2.8), indicating secondary organic aerosol formation might be significant during haze days. Correlation analysis between visibility and chemical species showed that the major scattering species were TC (total carbon) and sulfate in normal days and nitrate and TC in haze days, respectively. Simultaneously, correlation analysis between visibility and meteorological factors demonstrated that visibility increased with both temperature and wind speed, while it decreased with relative humidity. Furthermore, the relatively higher value of IcdP/(BghiP + IcdP) and the low value of Cmax, CPI, and BghiP/BeP in winter haze could be due to the growth of motor vehicle usage and energy consumption in winter.     

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.     

北京大气能见度的主要影响因子

利用北京市道面自动气象站、国家级自动气象站等多种观测数据分析北京地区2007—2015年能见度及其主要影响因子, 并挑选两次典型低能见度事件过程进行详细分析。从空间分布看, 北京西北地区能见度明显高于中心城区和东南大部地区。从时间分布看, 北京地区平均能见度最大值出现在5月, 最小值出现在7月; 日间的最低值多出现在06:00(北京时, 下同)左右, 冬季略向后推迟; 最高值多出现在16:00前后, 冬季略有提前。整体而言, 2007—2015年北京地区发生低能见度事件的概率为62.14%, 且发生低能见度的事件集中于1~5 km, 霾事件中干霾、湿霾的发生频率分别为86.13%和13.87%。能见度的主要影响因子为相对湿度、风速和PM_2.5浓度。其中, 能见度与风速呈正相关, 与相对湿度和PM_2.5浓度呈反相关。需要指出的是, 当相对湿度增加至80%, 能见度受PM_2.5浓度的影响程度在下降, 而主要受相对湿度的影响。基于所选个例, 当北京地区出现湿霾事件时, 能见度的恶化程度远高于干霾事件, 且PM_2.5浓度需比干霾事件时下降得更低才能有效改善能见度。     

Black carbon and chemical characteristics of PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript> at an urban site of North India

The concentrations of PM₁₀, PM_2.5 and their water-soluble ionic species were determined for the samples collected during January to December, 2007 at New Delhi (28.63° N, 77.18° E), India. The annual mean PM₁₀ and PM_2.5 concentrations (± standard deviation) were about 219 (± 84) and 97 (±56) μgm⁻³ respectively, about twice the prescribed Indian National Ambient Air Quality Standards values. The monthly average ratio of PM_2.5/PM₁₀ varied between 0.18 (June) and 0.86 (February) with an annual mean of ∼0.48 (±0.2), suggesting the dominance of coarser in summer and fine size particles in winter. The difference between the concentrations of PM₁₀ and PM_2.5, is deemed as the contribution of the coarse fraction (PM_10−2.5). The analyzed coarse fractions mainly composed of secondary inorganic aerosols species (16.0 μgm⁻³, 13.07%), mineral matter (12.32 μgm⁻³, 10.06%) and salt particles (4.92 μgm⁻³, 4.02%). PM_2.5 are mainly made up of undetermined fractions (39.46 μgm⁻³, 40.9%), secondary inorganic aerosols (26.15 μgm⁻³, 27.1%), salt aerosols (22.48 μgm⁻³, 23.3%) and mineral matter (8.41 μgm⁻³, 8.7%). The black carbon aerosols concentrations measured at a nearby (∼300 m) location to aerosol sampling site, registered an annual mean of ∼14 (±12) μgm⁻³, which is significantly large compared to those observed at other locations in India. The source identifications are made for the ionic species in PM₁₀ and PM_2.5. The results are discussed by way of correlations and factor analyses. The significant correlations of Cl⁻, SO₄²⁻, K⁺, Na⁺, Ca²⁺, NO₃⁻ and Mg²⁺ with PM_2.5 on one hand and Mg²⁺ with PM₁₀ on the other suggest the dominance of anthropogenic and soil origin aerosols in Delhi.     

Microscopic morphology and size distribution of particles in PM<Subscript>2.5</Subscript> of Guangzhou City

Samples of airborne PM_2.5 particles in Guangzhou urban area were collected during the autumn of 2006 and the spring of 2007. The morphologies and elemental compositions of individual particles were determined by Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectrometer (SEM-EDX). The obtained images were further analyzed for size distribution by an image analysis system. Based on the morphology, particles in PM_2.5 were classified into four groups: soot aggregates, minerals, fly ash and others. The amount of soot aggregates and minerals were higher than that of fly ashes. The distributions of particles by number and size in two seasons were bimodal with 90% less than 1.0 μm in diameter. The primary peak from the autumn samples was in the size range of 0.4 ~ 0.5 μm, and 0.3 ~ 0.4 μm for the spring samples. More soot aggregates (36.1%) and minerals (61.5%) were found than fly ash (2.4%) in autumn, but soot aggregates (89.9%) was the dominant particle type in spring. The size distribution of particles according to the volume was generally opposite to that according to the number. Particles less than 1.0 μm were as high as 89.5% in number but contributed only 18.9% in volume, indicating that fine particles contributed relatively little in volume although existing in large numbers.     

有霾和无霾时宁波市大气混合层高度的日变化特征

根据2007—2013年宁波市每日8次地面观测气象资料,运用罗氏法和统计分析法计算大气混合层高度,分析其在霾日和非霾日的不同日变化特征。结果表明宁波市霾日与非霾日混合层高度均呈白天高,夜晚低的日变化特征,夏季两者差值的日变化波动最明显,波峰时间比其他季节晚3 h。混合层高度日变化趋势与风速、气温、能见度趋于一致,霾等级越重,混合层高度越低。霾日与非霾日的气温差值除冬季呈正变温外,其他季节呈负变温,冬季14时差值最小,夜间加大,春夏季凌晨差值最小,14时最大,秋季波动不明显;风速差值除冬季夜间为正值外,其余季节为负值,秋冬季差值最小、夏季最大。大气处于不稳定状态时,混合层高度随着稳定度增加而逐渐处于稳定状态时,随着稳定度增加而降低,中性大气是宁波易致霾的大气层结。霾日与非霾日大气稳定度表现不一致,中午霾日中性大气占多数,非霾日则是不稳定大气;夜间霾日稳定—弱稳定大气和中性大气所占比例相当,非霾日稳定—弱稳定大气占多数。另外,PM_(2.5)浓度在霾日和非霾日均为白天低、夜间高的日变化特征,但霾日波动大,波峰时间晚于非霾日2 h,峰值浓度也高于非霾日2.7倍;早晨或下午到上半夜是霾日的PM_(2.5)浓度两个上升时段,上午为下降时段;非霾日的两个浓度缓升(降)时段分别出现凌晨和下午(上午和前半夜)。研究成果有助于预报员了解大气混合层高度及其对霾的可能影响,从而提高霾预报预警能力。     

Size distributions and dry deposition fluxes of water-soluble inorganic nitrogen in atmospheric aerosols in Xiamen Bay,China

Size-segregated aerosol particles were collected using a high volume MOUDI sampler at a coastal urban site in Xiamen Bay, China, from March 2018 to June 2020 to examine the seasonal characteristics of aerosol and water-soluble inorganic ions (WSIIs) and the dry deposition of nitrogen species. During the study period, the annual average concentrations of PM₁, PM_2.5, PM₁₀, and TSP were 14.8?±?5.6, 21.1?±?9.0, 35.4?±?14.2 μg m^?3, and 45.2?±?21.3 μg m^?3, respectively. The seasonal variations of aerosol concentrations were impacted by the monsoon with the lowest value in summer and the higher values in other seasons. For WSIIs, the annual average concentrations were 6.3?±?3.3, 2.1?±?1.2, 3.3?±?1.5, and 1.6?±?0.8 μg m^?3 in PM₁, PM_1-2.5, PM_2.5–10, and PM_>10, respectively. In addition, pronounced seasonal variations of WSIIs in PM₁ and PM_1-2.5 were observed, with the highest concentration in spring-winter and the lowest in summer. The size distribution showed that SO₄^2?, NH₄⁺ and K⁺ were consistently present in the submicron particles while Ca²⁺, Mg²⁺, Na⁺ and Cl^? mainly accumulated in the size range of 2.5–10 μm, reflecting their different dominant sources. In spring, fall and winter, a bimodal distribution of NO₃^? was observed with one peak at 2.5–10 μm and another peak at 0.44–1 μm. In summer, however, the fine mode peak disappeared, likely due to the unfavorable conditions for the formation of NH₄NO₃. For NH₄⁺ and SO₄^2?, their dominant peak at 0.25–0.44 μm in summer and fall shifted to 0.44–1 μm in spring and winter. Although the concentration of NO₃–N was lower than NH₄–N, the dry deposition flux of NO₃–N (35.77?±?24.49 μmol N m^?2 d^?1) was much higher than that of NH₄–N (10.95?±?11.89 μmol N m^?2 d^?1), mainly due to the larger deposition velocities of NO₃–N. The contribution of sea-salt particles to the total particulate inorganic N deposition was estimated to be 23.9—52.8%. Dry deposition of particulate inorganic N accounted for 0.95% of other terrestrial N influxes. The annual total N deposition can create a new productivity of 3.55 mgC m^?2 d^?1, accounting for 1.3–4.7% of the primary productivity in Xiamen Bay. In light of these results, atmospheric N deposition could have a significant influence on biogeochemistry cycle of nutrients with respect to projected increase of anthropogenic emissions from mobile sources in coastal region.

     

Relative contributions of boundary-layer meteorological factors to the explosive growth of PM<Subscript>2.5</Subscript> during the red-alert heavy pollution episodes in Beijing in December 2016

Based on observations of urban mass concentration of fine particulate matter smaller than 2.5 μm in diameter (PM_2.5), ground meteorological data, vertical measurements of winds, temperature, and relative humidity (RH), and ECMWF reanalysis data, the major changes in the vertical structures of meteorological factors in the boundary layer (BL) during the heavy aerosol pollution episodes (HPEs) that occurred in winter 2016 in the urban Beijing area were analyzed. The HPEs are divided into two stages: the transport of pollutants under prevailing southerly winds, known as the transport stage (TS), and the PM_2.5 explosive growth and pollution accumulation period characterized by a temperature inversion with low winds and high RH in the lower BL, known as the cumulative stage (CS). During the TS, a surface high lies south of Beijing, and pollutants are transported northwards. During the CS, a stable BL forms and is characterized by weak winds, temperature inversion, and moisture accumulation. Stable atmospheric stratification featured with light/calm winds and accumulated moisture (RH > 80%) below 250 m at the beginning of the CS is closely associated with the inversion, which is strengthened by the considerable decrease in near-surface air temperature due to the interaction between aerosols and radiation after the aerosol pollution occurs. A significant increase in the PLAM (Parameter Linking Aerosol Pollution and Meteorological Elements) index is found, which is linearly related to PM mass change. During the first 10 h of the CS, the more stable BL contributes approximately 84% of the explosive growth of PM_2.5 mass. Additional accumulated near-surface moisture caused by the ground temperature decrease, weak turbulent diffusion, low BL height, and inhibited vertical mixing of water vapor is conducive to the secondary aerosol formation through chemical reactions, including liquid phase and heterogeneous reactions, which further increases the PM_2.5 concentration levels. The contribution of these reaction mechanisms to the explosive growth of PM_2.5 mass during the early CS and subsequent pollution accumulation requires further investigation.     

Size distributions of ambient air particles and enrichment factor analyses of metallic elements at Taichung Harbor near the Taiwan Strait

This work attempts to characterize metallic elements associated with atmospheric particulate matter on a dry deposition plate, a TE-PUF high-volume air sampler and a universal air sampler. Dry deposition fluxes of particulates and concentrations of total suspended particulate, fine (PM_2.5) and coarse (PM_2.5–10) particulate matters were collected at Taichung harbor sampling sites from August 2004 to January 2005. Chemical analyses of metallic elements were made using a flame atomic absorption spectrophotometer coupled with hollow cathode lamps. Concentrations of metal elements in the forms of coarse particles and fine particles as well as the coarse/fine particulate ratios were presented. Statistical methods such as correlation analysis, principal component analysis and enrichment factor analysis were performed to compare the chemical components and identify possible emission sources at the sampling sites. Metallic elements of Cu, Zn, Pb, Cr, Ni and Mg had higher EF_crust ratios in winter and spring than in summer and autumn. Diurnal and nocturnal variations of metallic element concentrations in fine and coarse particles were also discussed.     

北京不同区域气溶胶辐射效应

采用大气辐射传输模式SES2以及2013年1月—2015年10月欧洲中期天气预报中心细网格再分析资料计算了北京地区4个观测站地面接收的短波辐射通量,分析了晴天和云天北京城郊气溶胶对总辐射的定量影响时空变化特征。结果表明:北京城区和近郊区气溶胶对总辐射的影响约为远郊区的2倍,北京南部和西部气溶胶对辐射的影响较大,晴天和云天北京城区和近郊区气溶胶对总辐射的削减值分别为146.23~180.99 W·m-2和202.11~217.02 W·m-2,晴天总辐射削减空间差异较大;秋冬季气溶胶对总辐射的影响明显大于春夏季,北京市观象台秋冬季气溶胶对总辐射的削减作用最大可达60%,较春夏季高10%~20%;北京城郊总辐射和直接辐射削减率与气溶胶光学厚度变化均呈线性关系,近地面PM_2.5浓度对辐射的影响不容忽视。     

Comparison of Ozone and PM2.5 Concentrations over Urban,Suburban, and Background Sites in China

Surface ozone (O₃) and fine particulate matter (PM_2.5) are dominant air pollutants in China. Concentrations of these pollutants can show significant differences between urban and nonurban areas. However, such contrast has never been explored on the country level. This study investigates the spatiotemporal characteristics of urban-to-suburban and urban-to-background difference for O₃ (Δ[O₃]) and PM_2.5 (Δ[PM_2.5]) concentrations in China using monitoring data from 1171 urban, 110 suburban, and 15 background sites built by the China National Environmental Monitoring Center (CNEMC). On the annual mean basis, the urban-to-suburban Δ[O₃] is ?3.7 ppbv in Beijing–Tianjin–Hebei, 1.0 ppbv in the Yangtze River Delta, ?3.5 ppbv in the Pearl River Delta, and ?3.8 ppbv in the Sichuan Basin. On the contrary, the urban-to-suburban Δ[PM_2.5] is 15.8, ?0.3, 3.5 and 2.4 μg m^?3 in those areas, respectively. The urban-to-suburban contrast is more significant in winter for both Δ[O₃] and Δ[PM_2.5]. In eastern China, urban-to-background differences are also moderate during summer, with ?5.1 to 6.8 ppbv for Δ[O₃] and ?0.1 to 22.5 μg m^?3 for Δ[PM_2.5]. However, such contrasts are much larger in winter, with ?22.2 to 5.5 ppbv for Δ[O₃] and 3.1 to 82.3 μg m^?3 for Δ[PM_2.5]. Since the urban region accounts for only 2% of the whole country’s area, the urban-dominant air quality data from the CNEMC network may overestimate winter [PM_2.5] but underestimate winter [O₃] over the vast domain of China. The study suggests that the CNEMC monitoring data should be used with caution for evaluating chemical models and assessing ecosystem health, which require more data outside urban areas.     

Characteristics of Carbonaceous Particles in Beijing During Winter and Summer 2003

Campaigns were conducted to measure Organic Carbon (OC) and Elemental Carbon (EC) in PM2.5 during winter and summer 2003 in Beijing. Modest differences of PM2.5 and PM10 mean concentrations were observed between the winter and summer campaigns. The mean PM2.5/PM10 ratio in both seasons was around 60%, indicating PM2.5 contributed significantly to PM10. The mean concentrations of OC and EC in PM2.5 were 11.2±7.5 and 6.0±5.0μg m-3 for the winter campaign, and 9.4±2.1 and 4.3±3.0 μg m-3 for the summer campaign, respectively. Diurnal concentrations of OC and EC in PM2.5 were found high at night and low during the daytime in winter, and characterized by an obvious minimum in the summer afternoon. The mean OC/EC ratio was 1.87±0.09 for winter and Z39±0.49 for summer. The higher OC/EC ratio in summer indicates some formation of Secondary Organic Carbon (SOC). The estimated SOC was 2.8 μg m-3 for winter and 4.2μg m-3 for summer.     

Assessment of PM<Subscript>2.5</Subscript> chemical compositions in Delhi: primary vs secondary emissions and contribution to light extinction coefficient and visibility degradation

Haze-fog conditions over northern India are associated with visibility degradation and severe attenuation of solar radiation by airborne particles with various chemical compositions. PM_2.5 samples have been collected in Delhi, India from December 2011 to November 2012 and analyzed for carbonaceous and inorganic species. PM₁₀ measurements were made simultaneously such that PM_10–2.5 could be estimated by difference. This study analyzes the temporal variation of PM_2.5 and carbonaceous particles (CP), focusing on identification of the primary and secondary aerosol emissions, estimations of light extinction coefficient (b_ext) and the contributions by the major PM_2.5 chemical components. The annual mean concentrations of PM_2.5, organic carbon (OC), elemental carbon (EC) and PM_10–2.5 were found to be 153.6 ± 59.8, 33.5 ± 15.9, 6.9 ± 3.9 and 91.1 ± 99.9 μg m^?3, respectively. Total CP, secondary organic aerosols and major anions (e.g., SO₄ ^2? and NO₃ ^?) maximize during the post-monsoon and winter due to fossil fuel combustion and biomass burning. PM_10–2.5 is more abundant during the pre-monsoon and post-monsoon. The OC/EC varies from 2.45 to 9.26 (mean of 5.18 ± 1.47), indicating the influence of multiple combustion sources. The b_ext exhibits highest values (910 ± 280 and 1221 ± 371 Mm^?1) in post-monsoon and winter and lowest in monsoon (363 ± 110 and 457 ± 133 Mm^?1) as estimated via the original and revised IMPROVE algorithms, respectively. Organic matter (OM =1.6 × OC) accounts for ~39 % and ~48 % of the b_ext, followed by (NH₄)₂SO₄ (~21 % and ~24 %) and EC (~13 % and ~10 %), according to the original and revised algorithms, respectively. The b_ext estimates via the two IMPROVE versions are highly correlated (R² = 0.95, root mean square error = 38 % and mean bias error = 28 %) and are strongly related to visibility impairment (r = ?0.72), mostly associated with anthropogenic rather than natural PM contributions. Therefore, reduction of CP and precursor gas emissions represents an urgent opportunity for air quality improvement across Delhi.     

Temporal Variability in Fine Carbonaceous Aerosol over Two Years in Two Megacities： Beijing and Toronto

Time-series of weekly total carbon(TC)concentrations of fine aerosol particles(PM2.5)in Beijing and Toronto were compared to investigate their respective levels and temporal patterns over two years from August 2001 through July 2003.In addition to this comparison,differences in the factors contributing to the observed concentrations and their temporal variations are discussed.Based upon past knowledge about the two megacities with highly contrasting air pollutant levels,it is not surprising that the average TC concentration in Beijing(31.5μg C m-3)was greater than that in Toronto by a factor of 8.3.Despite their large concentration differences,in both cities TC comprised a similarly large component of PM2.5.TC concentrations exhibited very different seasonal patterns between the two cities.In Beijing,TC experienced higher levels and greater weekly fluctuations in winter whereas in Toronto this behavior was seen in summer. As a result,the greatest gap in TC concentrations between Beijing and Toronto(by a factor of 12.7) occurred in winter,while the smallest gap(a factor of 4.6)was in summer.In Beijing,seasonal variations in the emissions probably played a greater role than meteorology in influencing the TC seasonality,while in Toronto during the warm months more than 80%of the hourly winds were recorded from the south,along with many potential anthropogenic sources for the days with high TC concentrations.This comparison of the differences provides insight into the major factors affecting carbonaceous aerosol in each city.     

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.     

江苏地区连续性雾霾天气的污染物浓度变化和特征分析

针对2013年1月江苏淮安地区发生的一次连续性雾霾天气过程,分析该天气过程中PM10和PM2.5的质量浓度演变特征、能见度与气象要素之间的关系、中低层环流特征以及污染物来源。结果表明:雾霾期间PM10和PM2.5质量浓度最低值出现在05:00至07:00(北京时间,下同)和13:00至17:00,最高值出现在21:00至23:00,PM10和PM2.5质量浓度并非同时达到极大值;持续变化较小的气压梯度、较低的风速、相对湿度的增大以及PM2.5和PM10质量浓度的增高是雾霾发生发展的必要条件;能见度与气压、相对湿度、PM2.5质量浓度的相关性较好,建立回归方程,对能见度的整体变化趋势拟合效果较好;高空环流形势平稳、中低层的暖平流、持续稳定少动的地面高压场分布为雾霾天气的持续发生发展提供了有利的形势背景;稳定的层结结构、中低层偏东及偏东北方向气团的输送、本地污染源以及严重的空气污染是此次过程中能见度偏低、霾天数较多的主要原因。     

Carbonaceous and inorganic species in PM<Subscript>10</Subscript> during wintertime over Giridih,Jharkhand (India)

Ambient concentrations of organic carbon (OC), elemental carbon (EC) and water soluble inorganic ionic components (WSIC) of PM₁₀ were studied at Giridih, Jharkhand, a sub-urban site near the Indo Gangatic Plain (IGP) of India during two consecutive winter seasons (November 2011–February 2012 and November 2012–February 2013). The abundance of carbonaceous and water soluble inorganic species of PM₁₀ was recorded at the study site of Giridih. During winter 2011–12, the average concentrations of PM₁₀, OC, EC and WSIC were 180.2?±?46.4; 37.2?±?6.2; 15.2?±?5.4 and 18.0?±?5.1 μg m^?3, respectively. Similar concentrations of PM₁₀, OC, EC and WSIC were also recorded during winter 2012–13. In the present case, a positive linear trend is observed between OC and EC at sampling site of Giridih indicates the coal burning, as well as dispersed coal powder and vehicular emissions may be the source of carbonaceous aerosols. The principal components analysis (PCA) also identifies the contribution of coal burning? +?soil dust, vehicular emissions?+?biomass burning and seconday aerosol to PM₁₀ mass concentration at the study site. Backward trajectoy and potential source contributing function (PSCF) analysis indicated that the aerosols being transported to Giridih from upwind IGP (Punjab, Haryana, Uttar Pradesh and Bihar) and surrounding region.     

江苏省雾霾天气特征分析

根据2007年1月—2013年12月江苏省国家基准气候站的逐日地面观测资料,分析了江苏省雾、霾日数的气候变化特征以及霾天气发生时的主要气象要素场特征。结果表明:(1)雾日数分布从江苏省东部向西部逐渐减少,霾分布由南向北逐渐递减。(2)年际变化上,雾日数呈现一定的波动,霾日数逐年增长。秋、冬两季雾日数较多;霾日数在夏季最少。雾、霾天气分别在08时和14时发生次数最多。(3)淮安中度霾居多,微风、高湿情况下霾发生概率最高,不同季节风向分布不同。(4)风速与能见度成正相关关系,春、夏季的相关性较差,秋、冬季相关性相对较好。能见度与相对湿度春、冬两季两者之间呈明显的线性负相关,而夏、秋季拟合曲线呈非线性负相关。     

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.