Constructing a Raman and surface-enhanced Raman scattering spectral reference library for fine-particle analysis

Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scattering (SERS) are often used to analyze the composition of fine particles to determine their physical and chemical properties as well as reaction mechanisms. However, there is no comprehensive Raman spectral library of fine particles. Furthermore, various studies that used SERS for fine-particle composition analysis showed that the uniqueness of the SERS substrates and different excitation wavelengths can produce a different spectrum for the same fine-particle component. To overcome this limitation, we conducted SERS experiments with a portable Raman spectrometer using two common SERS substrates (silver (Ag) foil and gold nanoparticles (Au NPs)) and a 785 nm laser. Herein, we introduced three main particle component types (sulfate-nitrate-ammonium (SNA), organic material, and soot) with a total of 39 chemical substances. We scanned the solid Raman, liquid Raman, and SERS spectra of these substances and constructed a fine-particle reference library containing 105 spectra. Spectral results indicated that for soot and SNA, the differences in characteristic peaks mainly originated from the solid-liquid phase transition; Ag foil had little effect on this difference, while the Au NPs caused a significant red shift in the peak positions of polycyclic aromatic hydrocarbons. Moreover, with various characteristic peak positions in the three types of spectra, we could quickly and correctly distinguish substances. We hope that this spectral library will aid in the future identification of fine particles.     

Intensified wintertime secondary inorganic aerosol formation during heavy haze pollution episodes (HPEs) in Beijing, China

Air pollution in China is complex, and the formation mechanism of chemical components in particulate matter is still unclear. This study selected three consecutive heavy haze pollution episodes (HPEs) during winter in Beijing for continuous field observation, including an episode with heavy air pollution under red alert. Clean days during the observation period were selected for comparison. The HPE characteristics of Beijing in winter were: under the influence of adverse meteorological conditions such as high relative humidity, temperature inversion and low wind speed; and strengthening of secondary transformation reactions, which further intensified the accumulation of secondary aerosols and other pollutants, promoting the explosive growth of PM_2.5. PM_2.5/CO values, as indicators of the contribution of secondary transformation in PM_2.5, were approximately 2 times higher in the HPEs than the average PM_2.5/CO during the clean period. The secondary inorganic aerosols (sulfate nitrate and ammonium salt) were significantly enhanced during the HPEs, and the conversion coefficients were remarkably improved. In addition, it is interesting to observe that the production of sulfate tended to exceed that of nitrate in the late stage of all three HPEs. The existence of aqueous phase reactions led to the explosive growth sulfur oxidation ratio (SOR) and rapid generation of sulfate under high relative humidity (RH>70%).     

Physicochemical analysis of individual atmospheric fine particles based on effective surface-enhanced Raman spectroscopy

Fine particles associated with haze pollution threaten the health of more than 400 million people in China. It is therefore of great importance to thoroughly investigate and understand their composition. To determine the physicochemical properties in atmospheric fine particles at the micrometer level, we described a sensitive and feasible surface-enhanced Raman scattering(SERS) method using Ag foil as a substrate. This novel method enhanced the Raman signal intensities up to 10,000 a.u. for ν(NO_3~-) in fine particles.The SERS effect of Ag foil was further studied experimentally and theoretically and found to have an enhancement factor of the order of ～10~4. Size-fractionated real particle samples with aerodynamic diameters of 0.4–2.5 μm were successfully collected on a heavy haze day,allowing ready observation of morphology and identification of chemical components, such as soot, nitrates, and sulfates. These results suggest that the Ag-foil-based SERS technique can be effectively used to determine the microscopic characteristics of individual fine particles, which will help to understand haze formation mechanisms and formulate governance policies.     

太原市冬季灰霾期间大气细颗粒物化学成分特征

研究了太原市灰霾发生期间大气PM2.5质量浓度和化学成分变化规律.采样时间为2011年12月27日16:00~2012年1月3日04:00,使用TH-150C中流量大气PM2.5采样器(采样膜为直径90mm的石英纤维滤膜)在山西大学环境科学研究所5层楼顶每隔4h采样一次,得到灰霾样品34个,非灰霾样品5个.采样期间对大气PM2.5质量浓度进行实时监测.结果表明:灰霾期间(初起、进展、鼎盛、减弱4个阶段)大气PM2.5平均浓度达(692±272)μg/m3,是非灰霾期间(即灰霾消失阶段) (54±12)μg/m3的12.8倍;在灰霾发生期间,大气PM2.5中Hg、Pb、As等重金属污染物、OC以及水溶性无机离子SO42-、NO3－、NH4+、K+、Cl－、F－浓度呈现相似的变化趋势,即在灰霾初起、进展阶段不断增加,在灰霾鼎盛期达到最大值,随后随着灰霾的减弱和消失而不断下降,最终降到一个较低的水平;而与燃煤关系不大的Zn元素、Ca2+、Mg2+等在灰霾各个时期浓度变化较小.以上结果说明冬季灰霾天气使太原市大气PM2.5浓度显著上升,并增加PM2.5中重金属、有机物和二次气溶胶含量,使其化学成分发生改变,同时也反映了冬季燃煤和生物质燃烧对太原市大气PM2.5的化学组成影响大于交通源和土壤扬尘.     

Enhanced mixing state of black carbon with nitrate in single particles during haze periods in Zhengzhou, China

Black carbon（BC） plays an important role in air quality and climate change, which is closely associated with its mixing state and chemical compositions. In this work the mixing state of BC-containing single particles was investigated to explore the evolution process of ambient BC particles using a single particle aerosol mass spectrometer（SPAMS） in March 2018 in Zhengzhou, China. The BC-containing particles accounted for 61.4% of total detected ambient single particles and were classified into f...     

Impact of transport of fine and ultrafine particles from open biomass burning on air quality during 2019 Bangkok haze episode

Transboundary and domestic aerosol transport during 2018–2019 affecting Bangkok air quality has been investigated. Physicochemical characteristics of size-segregated ambient particles down to nano-particles collected during 2017 non-haze and 2018–2019 haze periods were analyzed. The average PM_2.5 concentrations at KU and KMUTNB sites in Bangkok, Thailand during the haze periods were about 4 times higher than in non-haze periods. The highest average organic carbon and elemental carbon ...     

Atmospheric fine particles in a typical coastal port of Yangtze River Delta

In recent decades, coastal ports have experienced rapid development and become an important economic and ecological hub in China. Atmospheric particle is a research hotspot in atmospheric environmental sciences in inland regions. However, few studies on the atmospheric particle were conducted in coastal port areas in China, which indeed suffers atmospheric particle pollution. Lack of the physicochemical characteristics of fine particles serves as an obstacle toward the accurate control for air pollution in the coastal port area in China. Here, a field observation was conducted in an important coastal port city in Yangtze River Delta from March 6 to March 19, 2019. The average PM_2.5 concentration was 63.7 ± 27.8 μg/m³ and NO₃^—, SO₄^2—, NH₄⁺, and organic matter accounted for ~60% of PM_2.5. Fe was the most abundant trace metal element and V as the ship emission indicator was detected. Transmission electron microscopy images showed that SK-rich, soot, Fe, SK-soot and SK-Fe were the major individual particles in the coastal port. V and soluble Fe were detected in sulfate coating of SK-Fe particles. We found that anthropogenic emissions, marine sea salt, and secondary atmosphere process were the major sources of fine particles. Backward trajectory analysis indicated that the dominant air masses were marine air mass, inland air mass from northern Zhejiang and inland-marine mixed air mass from Shandong and Shanghai during the sampling period. The findings can help us better understand the physicochemical properties of atmospheric fine particles in the coastal port of Eastern China.     

Aerosol scattering coefficients and major chemical compositions of fine particles observed at a rural site in the central Pearl River Delta, South China

During November-December 2010 aerosol scattering coefficients were monitored using a single-waved (525 nm) Nephelometer at a regional monitoring station in the central Pearl River Delta region and 24-hr fine particle (PM_2.5) samples were also collected during the period using quartz filters for the analysis of major chemical components including organic carbon (OC), elemental carbon (EC), sulfate, nitrate and ammonium. In average, these five components accounted for about 85% of PM_2.5 mass and contributed 42% (OC), 19% (SO₄^2-), 12% (NO₃^-), 8.4% (NH₄⁺) and 3.7% (EC), to PM_2.5 mass. A relatively higher mass scattering efficiency of 5.3 m²/g was obtained for fine particles based on the linear regression between scattering coefficients and PM_2.5 mass concentrations. Chemical extinction budget based on IMPROVE approach revealed that ammonium sulfate, particulate organic matter, ammonium nitrate and EC in average contributed about 32%, 28%, 20% and 6% to the light extinction coefficients, respectively.     

重庆市主城区大气细颗粒物污染特征与来源解析

重庆市主城区大气细颗粒物(PM_(2.5))浓度从1990s的100μg·m~(-3)下降至当前的约70μg·m~(-3),但仍高于环境标准限值.为探讨重庆市主城区PM_(2.5)化学组成与来源特征,于2012—2013年在渝北区大气超级站利用四通道采样仪连续采集了颗粒物样品,分析了其中水溶性离子、碳质组分和无机元素含量.采样期间,重庆市主城区大气PM_(10)和PM_(2.5)的年日均浓度分别为103.9和75.3μg·m~(-3),扩散条件不利的冬季,细颗粒物污染较为严重.受静稳天气影响的1月和2月,受沙尘影响的3月,及二次转化显著的6月是重庆市细颗粒物污染较重的月份.重庆市PM_(2.5)组成以有机物(OM,30.8%)为主,其次为硫酸盐(SO_4~(2-),23.0%)、硝酸盐(NO_3~-,11.7%)、铵盐(NH_4~+,10.9%)、地壳物质(Soil,8.2%)、元素碳(EC,5.2%)、K~+(1.1%)、Cl~-(1.0%)和微量元素(Trace,0.6%).较高的SO_4~(2-)浓度和逐步上升的[NO_3~-]/[SO_4~(2-)]比值反映了重庆市燃煤污染较重,同时机动车污染比例逐步增加.采用主因子分析/绝对主因子得分法解析了重庆城区细颗粒物5类主要来源是:二次粒子(41.7%)、燃煤(15.6%)、建筑/道路尘(12.4%)、土壤尘(11.0%)和工业尘(10.4%),通过各污染源季节变化及与其他结果对比,该源解析结果能够较可靠反映重庆市细颗粒物的来源信息.     

成都一次霾过程中颗粒物消光作用的垂直变化

基于2017年1月4~7日成都地区一次重霾过程中,颗粒物粒径谱的垂直加密观测和激光雷达同步观测数据,利用Mie散射理论计算颗粒物消光系数并与激光雷达反演结果对比,计算了不同粒径谱颗粒物消光系数以及消光贡献率.分析表明：重霾期间,在不同边界层高度上颗粒物消光系数表现为PM₁ > PM_2.5~10 > PM_1~2.5 > PM _{> 10},其中PM₁的消光贡献率整体上维持在49.5%~69.4%,是本次重霾过程中影响颗粒物消光系数大小的主要因子.在大气边界层内,不同粒径谱颗粒物消光作用呈现出显著垂直变化和昼夜差异,白天在600m以下和700~1100m之间颗粒物消光系数出现高值区;夜间颗粒物消光系数整体上随高度呈现出明显递减趋势,在1100m处出现高值.此外,夜间在200m以下颗粒物消光系数明显大于白天,且PM_>1的消光贡献率也明显大于白天.整体上,PM₁消光贡献率随高度递增,而PM_>1消光贡献率随高度递减.     

Variability of turbulence dispersion characteristics during heavy haze process: A case study in Beijing

The turbulent standard deviations and the turbulent third-order and fourth-order moments are the key turbulence dispersion parameters in Lagrangian dispersion models. However, the characteristics of these parameters under heavy haze conditions in urban areas have not been fully investigated, and the commonly used similarity relations of these parameters in models were based on observations in highly flat and sparsely populated areas. In this paper, the vertical profiles of these parameters and their local similarity relations under heavy haze conditions in the wintertime of Beijing have been analyzed by using data collected at a 325-m meteorological tower. The heavy haze process has been divided into three stages: transport stage (TS), cumulative stage (CS), and dispersion stage (DS). Results show that the turbulent dispersion parameters behave differently during three stages. In the TS and DS, the maxima appear in the profiles of the turbulent standard deviations above the urban canopy; in the CS, the turbulent standard deviation are almost constant with height. The analysis of the third and fourth order moments shows that the wind velocities above the urban canopy in the TS deviate from the Gaussian distribution more significantly than those in the CS and DS. The local similarity relations of the turbulent dispersion parameters in the TS, especially for the longitudinal wind components, are normally different from those in the CS and DS. Thus, different from the common assumptions in Lagrangian models, the turbulence dispersion in horizontal directions is anisotropic and should be parameterized by multiple similarity relations under heavy haze conditions.     

北京城区2007~2012年细颗粒物数浓度时空演化

为反映近年来北京城区细颗粒物数浓度时空演化过程,利用MODEL 3886GEO-α手持式激光粒子计数仪连续采集了2007~2012年北京城区93个采样点 6月上旬~7月上旬(非采暖期)和12月上旬~次年的1月上旬(采暖期)细粒径颗粒物PM (0.3、0.3~0.5、0.5~1.0) 的粒子数浓度数据,然后在地统计和空间分析方法的基础上,探究了北京城区细颗粒物数浓度的时空演化特征.结果表明,PM0.3在采暖期的数值均高于其在非采暖期的浓度值,而PM0.3~0.5和PM0.5~1.0在两个不同的采样期浓度值有高有低;采暖期不同下垫面细颗粒浓度差异较明显,而非采暖期下垫面类型对细颗粒浓度的影响相对较弱;非采暖期,北京城区南部的丰台区和东部的朝阳区细颗粒物污染最严重,市中心次之,而北部的海淀区和西部的石景山区污染相对较轻;采暖期,北京城区细颗粒物污染主要集中在朝阳区的东部和东南部,以及市中心及其周边区域.     

Seasonal differences in sources and formation processes of PM2.5 nitrate in an urban environment of North China

Nitrate (NO₃⁻) has been the dominant ion of secondary inorganic aerosols (SIAs) in PM_2.5 in North China. Tracking the formation mechanisms and sources of particulate nitrate are vital to mitigate air pollution. In this study, PM_2.5 samples in winter (January 2020) and in summer (June 2020) were collected in Jiaozuo, China, and water-soluble ions and (δ¹⁵N, δ¹⁸O)-NO₃⁻ were analyzed. The results showed that the increase of NO₃⁻ concentrations was the most remarkable with increasing PM_2.5 pollution level. δ¹⁸O-NO₃⁻ values for winter samples (82.7‰ to 103.9‰) were close to calculated δ¹⁸O-HNO₃ (103‰ ± 0.8‰) values by N₂O₅ pathway, while δ¹⁸O-NO₃⁻ values (67.8‰ to 85.7‰) for summer samples were close to calculated δ¹⁸O-HNO₃ values (61‰ ± 0.8‰) by OH oxidation pathway, suggesting that PM_2.5 nitrate is largely from N₂O₅ pathway in winter, while is largely from OH pathway in summer. Averaged fractional contributions of P_N2O5+H2O were 70% and 39% in winter and summer sampling periods, respectively, those of P_OH were 30% and 61%, respectively. Higher δ¹⁵N-NO₃⁻ values for winter samples (3.0‰ to 14.4‰) than those for summer samples (-3.7‰ to 8.6‰) might be due to more contributions from coal combustion in winter. Coal combustion (31% ± 9%, 25% ± 9% in winter and summer, respectively) and biomass burning (30% ± 12%, 36% ± 12% in winter and summer, respectively) were the main sources using Bayesian mixing model. These results provided clear evidence of particulate nitrate formation and sources under different PM_2.5 levels, and aided in reducing atmospheric nitrate in urban environments.     

元宵节期间北京PM_(2.5)单颗粒的物理化学特征

采集2014年元宵节期间北京PM2.5样品,使用场发射扫锚电镜-能谱仪观察北京PM2.5单颗粒的显微形貌和元素组成,并利用图像分析系统对PM2.5的粒径进行分析.结果表明:PM2.5的单颗粒类型以烟尘集合体、矿物颗粒和飞灰为主;烟花爆竹燃放产生的PM2.5是造成元宵节期间北京PM2.5浓度升高的主要原因;PM2.5中总颗粒物个数呈现先升高后降低的趋势;元宵节期间北京PM2.5中大部分颗粒物的粒径小于0.7μm;然而,重污染天气PM2.5中粒径大于0.7μm颗粒物的数量明显高于轻污染天气.     

Cross-boundary transport and source apportionment for PM2.5 in a typical industrial city in the Hebei Province, China: A modeling study

Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain. In this study, an industrial district (Shahe City) with a large glass manufacturing sector was investigated to clarify the relative contribution of fine particulate matter (PM_2.5) to the city's high levels of pollution. The Nest Air Quality Prediction Model System (NAQPMS), paired with Weather Research and Forecasting (WRF), was adopted and applied with a spatial resolution of 5 km. During the study period, the mean mass concentrations of PM_2.5, SO₂, and NO₂ were observed to be 132.0, 76.1, and 55.5 μg/m³, respectively. The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level. The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4% of the city's total PM_2.5 concentration. This contribution increased to 73.9±21.2% when unfavorable meteorological conditions (high relative humidity, weak wind, and low planetary boundary layer height) were present; such conditions are more frequently associated with severe pollution (PM_2.5 ≥ 250 μg/m³). The contribution from Shahe was 52.3±21.6%. The source apportionment results showed that industry (47%), transportation (10%), power (17%), and residential (26%) sectors were the most important sources of PM_2.5 in Shahe. The glass factories (where chimney stack heights were normally < 70 m) in Shahe contributed 32.1% of the total PM_2.5 concentration in Shahe. With an increase in PM_2.5 concentration, the emissions from glass factories accumulated vertically and narrowed horizontally. At times when pollution levels were severe, the horizontally influenced area mainly covered Shahe. Furthermore, sensitivity tests indicated that reducing emissions by 20%, 40%, and 60% could lead to a decrease in the mass concentration of PM_2.5 of of 12.0%, 23.8%, and 35.5%, respectively.     

Formation mechanisms of nitrous acid (HONO) during the haze and non-haze periods in Beijing, China

As an important precursor of hydroxyl radical (OH), nitrous acid (HONO) plays a significant role in atmospheric chemistry. Here, an observation of HONO and relevant air pollutants in an urban site of Beijing from 14 to 28 April, 2017 was performed. Two distinct peaks of HONO concentrations occurred during the observation. In contrast, the concentration of particulate matter in the first period (period Ⅰ) was significantly higher than that in the second period (period Ⅱ). Comparing to HONO sources in the two periods, we found that the direct vehicle emission was an essential source of the ambient HONO during both periods at night, especially in period Ⅱ. The heterogeneous reaction of NO₂ was the dominant source in period Ⅰ, while the homogeneous reaction of NO with OH was more critical source at night in period Ⅱ. In the daytime, the heterogeneous reaction of NO₂ was a significant source and was confirmed by the good correlation coefficients (R²) between the unknown sources (P_unknown) with NO₂, PM_2.5, NO₂ × PM_2.5 in period Ⅰ. Moreover, when solar radiation and OH radicals were considered to explore unknown sources in the daytime, the enhanced correlation of P_unknown with photolysis rate of NO₂ and OH ($J_{{\mathrm{NO}}_2}$ × OH) were 0.93 in period Ⅰ, 0.95 in period Ⅱ. These excellent correlation coefficients suggested that the unknown sources released HONO highly related to the solar radiation and the variation of OH radicals.     

上海城区典型空气污染过程中细颗粒污染特征研究

采集了上海城区2009年10月10~21日期间2次空气污染过程的样品,在对污染过程分析的基础上,着重分析了PM2.5及其化学组分的变化,探讨了污染源及形成机制.研究表明,14日的灰霾过程主要由本地排放的污染物二次转化形成,PM2.5占PM10比重超过60%且PM2.5中离子组分含量高.17~19日的浮尘过程中,受北方沙尘影响本市粗颗粒浓度上升,PM2.5所占比重下降,二次离子组分从细颗粒物向粗颗粒物转移且Ca2+浓度上升,同时受到长江三角洲区域秸秆焚烧的影响,细颗粒物中K+, EC和OC含量高.因此,应在控制本地源排放的同时,加强对细颗粒尤其是二次细颗粒污染及其前体物的协同控制.     

Size, composition, and mixing state of individual aerosol particles in a South China coastal city

Aerosol samples were collected in summer in Macao,a coastal city of the Pearl River Delta Region in China.Morphology,size,elemental composition,and mixing state of individual aerosol particles were determined by scanning electron microscopy coupled energy dispersive X-ray(SEM/EDX) and transmission electron microscopy(TEM).Based on the morphologies of 5711 aerosol particles,they consist of soot(32%),mineral(17%),secondary(22%),and unknown fine particles(29%).The sizes of these particles were mostly distributed between 0.1 and 0.4 μm.Compositions of 202 mineral particles were obtained by SEM/EDX.Mineral particles were mainly classified into three types:Si-rich,Ca-rich,and Na-rich.The compositions of typical mineral particles can indicate their sources in sampling location.For example,mineral particles,collected along the main street,were associated with trace amounts of heavy metals,such as Zn,Ti,Mn,Ba,Pb,and As.TEM observations indicate that most Na-rich particles were aged sea salt particles(e.g.,Na2SO4 and NaNO3) which formed through heterogeneous chemical reactions between sea salt and acidic gases.Additionally,aging time of soot was short in Macao due to high humidity,high temperature,and high levels of sunlight in Macao.Most of soot and fine mineral dust particles were internally mixed with secondary particles.     

Study of aerosol characteristics and sources using MAX-DOAS measurement during haze at an urban site in the Fenwei Plain

Atmospheric aerosols have effects on atmospheric radiation assessments, global climate change, local air quality and visibility. In particular, aerosols are more likely transformed and accumulated in winter. In this paper, we used the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument to study the characteristics of aerosol type and contributions of PM_2.5 chemical components to aerosol extinction (AE), vertical distribution of aerosols, and source. From December 30, 2018 to January 27, 2019, we conducted MAX-DOAS observations on Sanmenxia. The proportion of PM_2.5 to PM₁₀ was 69.48%–95.39%, indicating that the aerosol particles were mainly fine particles. By analyzing the ion data and modifying Interagency Monitoring of Protected Visual Environments (IMPROVE) method, we found that nitrate was the largest contributor to AE, accounting for 31.51%, 28.98%, and 27.95% of AE on heavily polluted, polluted, and clean days, respectively. NH₄⁺, OC, and SO₄^2? were also major contributors to AE. The near-surface aerosol extinction retrieved from MAX-DOAS measurement the PM_2.5 and PM₁₀ concentrations measured by an Unmanned Aerial Vehicle (UAV) have the same trend in vertical distribution. AE increased about 3 times from surface to 500 m. With the backward trajectory of the air mass during the haze, we also found that the continuous heavy pollution was mainly caused by transport of polluted air from the northeast, then followed by local industrial emissions and other sources of emissions under continuous and steady weather conditions.     

Characterization of personal exposure concentration of fine particles for adults and children exposed to high ambient concentrations in Beijing, China

In China, the health risk from overexposure to particles is becoming an important public health concern. To investigate daily exposure characteristics to PM 2.5 with high ambient concentration in urban area, a personal exposure study was conducted for school children, and office workers in Beijing, China. For all participants (N = 114), the mean personal 24-hr exposure concentration was 102.5, 14.7, 0.093, 0.528, 0.934, 0.174 and 0.703 μg/m 3 for PM 2.5 , black carbon, Mn, Al, Ca, Pb, and Fe. Children's exposure concentrations of PM 2.5 were 4-5 times higher than those in related studies. The ambient concentration of PM 2.5 (128.5 μg/m 3 ) was significantly higher than the personal exposure concentration (P 0.05), and exceed the reference concentration (25 μg/m 3 ) of WHO air quality guideline. Good correlation relationships and significant differences were identified between ambient concentration and personal exposure concentration. The relationships indicate that the ambient concentration is the main factor influencing personal exposure concentration, but is not a good indicator of personal exposure concentration. Outdoor activities (commute mode, exposure to heating, workday or weekend travel) influenced personal exposure concentrations significantly, but the magnitude of the influence from indoor activities (exposure to cooking) was masked by the high ambient concentrations.