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1.
针对受体模型对大气PM2.5中二次无机、有机气溶胶不能给出有效源贡献的问题,建立了一种基于污染源清单的化学质量平衡(Inventory-Chemical Mass Balance,I-CMB)颗粒物源解析受体模型,代入北京市近年的污染物排放数据进行了解析应用。结果表明,燃煤是北京大气PM2.5的最大来源(占比约28.06%),其余依次为机动车(19.73%)、扬尘(17.88%)、工业(16.50%)、餐饮(3.43%)、植物(3.40%)。相比于传统的化学质量平衡法(Chemical Mass Balance,CMB),I-CMB的源解析过程对源成分谱的要求较低、抗干扰性更强,计算结果均衡、详尽,比较适合我国当前大气PM2.5控制的需求。  相似文献   

2.
Spokane, WA is prone to frequent particulate pollution episodes due to dust storms, biomass burning, and periods of stagnant meteorological conditions. Spokane is the location of a long-term study examining the association between health effects and chemical or physical constituents of particulate pollution. Positive matrix factorization (PMF) was used to deduce the sources of PM2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) at a residential site in Spokane from 1995 through 1997. A total of 16 elements in 945 daily PM2.5 samples were measured. The PMF results indicated that seven sources independently contribute to the observed PM2.5 mass: vegetative burning (44%), sulfate aerosol (19%), motor vehicle (11%), nitrate aerosol (9%), airborne soil (9%), chlorine-rich source (6%) and metal processing (3%). Conditional probability functions were computed using surface wind data and the PMF deduced mass contributions from each source and were used to identify local point sources. Concurrently measured carbon monoxide and nitrogen oxides were correlated with the PM2.5 from both motor vehicles and vegetative burning.  相似文献   

3.
Source identification for fine aerosols in Mammoth Cave National Park   总被引:1,自引:0,他引:1  
In this study, positive matrix factorization (PMF) was applied to the chemical composition data of the ambient PM2.5 collected at the Mammoth Cave National Park, an IMPROVE site in Kentucky. Eight individual carbon fractions, four organic carbons (OCs), pyrolyzed organic carbon (OP) and three elemental carbons (ECs), were provided to the analysis. Nine sources including the well-distinguished gasoline emission and diesel emission were identified. Also, the back trajectories indicated the crustal factor in this study were likely caused by Saharan dust storms in the summer. The apportionment of nine sources was: gasoline emission (6.7%), diesel emission (3.1%), summer secondary sulfate (49.0%), winter secondary sulfate (0.6%), OP-rich secondary sulfate (16.2%), secondary nitrate (2.8%), Intercontinental dust plus soil (4.9%), wood smoke (13.6%), and aged sea salt (3.2%). The results of this study will help regularize the pollution control strategies in rural areas of Kentucky and upper mid-western US while demonstrating the feasibility of applying carbon fractions to the source apportionment of rural upper-Midwestern areas.  相似文献   

4.
In this work, the influence of South Asian biomass burning emissions on O3 and PM2.5 concentrations over the Tibetan Plateau (TP) is investigated by using the regional climate chemistry transport model WRF-Chem. The simulation is validated by comparing meteorological fields and pollutant concentrations against in situ observations and gridded datasets, providing a clear perspective on the spatiotemporal variations of O3 and PM2.5 concentrations across the Indian subcontinent, including the Tibetan Plateau. Further sensitivity simulations and analyses show that emissions from South Asian biomass burning mainly affect local O3 concentrations. For example, contribution ratios were up to 20% in the Indo-Gangetic Plain during the pre-monsoon season but below 1% over the TP throughout the year 2016. In contrast, South Asian biomass burning emissions contributed more than 60% of PM2.5 concentration over the TP during the pre-monsoon season via significant contribution of primary PM2.5 components (black carbon and organic carbon) in western India that were lofted to the TP by westerly winds. Therefore, it is suggested that cutting emissions from South Asian biomass burning is necessary to alleviate aerosol pollution over the TP, especially during the pre-monsoon season.  相似文献   

5.
春季中国东部气溶胶化学组成及其分布的模拟研究   总被引:2,自引:0,他引:2  
本文利用区域空气质量模式RAQMS(Regional Air Quality Model System),对2009年春季中国东部气溶胶主要化学成分及其分布进行了模拟研究。与泰山站观测资料的对比结果显示,模式能比较合理地反映气溶胶浓度的逐日变化特征。整体上,模式对无机盐气溶胶的模拟好,分别高估和低估黑碳和有机碳气溶胶浓度,其原因与排放源、二次有机气溶胶化学机制和模式分辨率的不确定性有关。模拟结果显示,春季气溶胶浓度高值主要集中于华北、四川东部、长江中下游等地区。受东南亚生物质燃烧和大气输送的影响,中国的云南和广西等地区有机碳浓度高于中国其他地区。中国西北部沙尘浓度较高,而且向东输送并影响到中国东部和南方部分地区。中国东部的华北、四川东部、长江中下游等地PM2.5(空气动力学直径在2.5微米以下的颗粒物)污染严重,4月平均PM2.5浓度超过了我国日平均PM2.5浓度限值。中国东部泰山站的观测和模拟结果都显示近地面硝酸盐浓度超过硫酸盐,中国北部对流层中硝酸盐的柱含量也大于硫酸盐,而在中国南部则相反,这一方面与春季中国云量 南多北少的分布特征以及云内液相化学反应有关,另一方面也与南北温差对气溶胶形成的影响有关。就整个中国东部而言,虽然硫酸盐的柱含量(46 Gg)仍大于硝酸盐(42 Gg),但比较接近,反映出我国氮氧化物排放迅速增加的趋势。春季中国地区对流层中PM10(空气动力学直径在10微米以下的颗粒物)及其化学成分柱含量分别为:990.8 Gg(PM10),52.6 Gg(硫酸盐),48.2 Gg(硝酸盐),32.1 Gg(铵盐),22.9 Gg(黑碳)和74.1 Gg(有机碳),有机碳(OC)中一次有机碳(POC)和二次有机碳(SOC)分别占60%和40%,中国东部PM10中人为气溶胶和沙尘分别占30%和70%,反映了春季沙尘对我国大气气溶胶的重要贡献。  相似文献   

6.
A set of daily PM10 (n = 281) samples collected from April 2001 to April 2002 at a rural site (Erdemli), located on the coast of the Eastern Mediterranean, were analyzed applying Mass Closure (MC), absolute principal factor analysis (APFA) and Positive Matrix Factorization (PMF) to determine source contributions. The results from the three techniques were compared to identify the similarities and differences in the sources and source contributions. Source apportionment analysis indicated that PM10 were mainly originated from natural sources (sea salt + crustal ≈ 60%) whilst secondary aerosols and residual oil burning accounted for approximately 20% and 10% of the total PM10 mass, respectively. Calculations for sulfate showed that on average 8% and 12% of its total concentration were originated from sea salt and biogenic emissions, respectively. However, the contribution by biogenic emissions may reach up to a maximum of ~ 40% in the summer. Potential Source Contribution Function (PSCF) analysis for identification of source regions showed that the Saharan desert was the main source area for crustal components. For secondary aerosol components the analysis revealed one source region, (i.e. the south-Eastern Black Sea), whereas for residual oil, Western Europe and the western Balkans areas were found to be the main source regions.  相似文献   

7.
Concentrations of thirty-five trace elements in ambient fine particulate matter (PM2.5) were measured from September 2001 to January 2002 in Mira Loma, a semi-urban area in southern California. The most abundant species were found to be sulfur (S; 23% of the total trace element concentration), followed by Si, Fe, Ca, and Al (soil-related elements; 51% of the total). In general, total trace element concentrations were found to be significantly higher for the drier months of September and October, compared to December and January. Factor analysis, enrichment factor (EF) analysis, and ratio analysis (Al/Zn) revealed a significant contribution of soil-related sources to the ambient trace elements for PM2.5 in the study area. Other important contributors to the trace elements in ambient PM2.5 in Mira Loma included motor vehicle-related emissions (brake pads, lubricant oils, gasoline, and diesel combustion), secondary sulfates, sea salts, and biomass burning. The influence of sea salts on the study area was identified using a backward trajectory analysis.  相似文献   

8.
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, PM2.5 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 PM2.5 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 PM2.5 and PM10 were secondary sulphate, secondary nitrate and crustal material, whereas the higher load of the anthropogenic component in PM2.5 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.  相似文献   

9.
Zhang  Xiaoyu  Ji  Guixiang  Peng  Xiaowu  Kong  Lingya  Zhao  Xin  Ying  Rongrong  Yin  Wenjun  Xu  Tian  Cheng  Juan  Wang  Lin 《Journal of Atmospheric Chemistry》2022,79(2):101-115

In this study, 123 PM2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM2.5 concentration was 80.5?±?38.2 μg/m3, with higher PM2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM2.5 mass concentration, respectively. SO42?, NO3? and NH4+ were the dominant components, accounting for 40.2% of PM2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO3?/SO42? was 0.86?±?0.72, indicating that stationary sources play dominant role on PM2.5 concentration. The ratio of OC/EC was 2.9?±?1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively.

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10.
通过采集武汉市土壤风沙尘、建筑水泥尘、城市扬尘、餐饮源、生物质燃烧源、工业煤烟尘和电厂煤烟尘等7类源样品,并分析其碳组分、水溶性离子组分和无机元素组分,建立PM10和PM2.5源成分谱.研究表明,地壳元素Si、Ca、Al以及Fe等是土壤风沙尘的主要特征组分,其中Si是含量最高的成分,也是土壤风沙尘的标识组分.无组织建筑水泥尘中Si和Ca元素含量较高,将Ca元素作为无组织建筑水泥尘区别其他源类的重要元素,而有组织建筑水泥尘中OC、SO42-含量比无组织建筑水泥尘高.城市扬尘中Ca的含量相对较高,表明城市扬尘受到建筑水泥尘影响较多.生物质燃烧源成分谱中OC的含量远高于成分谱中其他组分,另外Cl-和K的平均含量也较高,K一般为生物质源的特征元素.  相似文献   

11.
An extensive aerosol sampling program was conducted during January-December 2006 over Kolkata (22o33?? N and 88o20?? E), a mega-city in eastern India in order to understand the sources, distributions and properties of atmospheric fine mode aerosol (PM2.5). The primary focus of this study is to determine the relative contribution of natural and anthropogenic as well as local and transported components to the total fine mode aerosol loading and their seasonal distributions over the metropolis. The average concentrations of fine mode aerosol was found to be 71.2?±?25.2???gm-3 varying between 34.5???gm-3 in monsoon and 112.6???gm-3 in winter. The formation pathways of major secondary aerosol components like nitrate and sulphate in different seasons are discussed. A long range transport of dust aerosol from arid and semi-arid regions of western India and beyond was observed during pre-monsoon which significantly enriched the total aerosol concentration. Vehicular emissions, biomass burning and transported dust particles were the major sources of PM2.5 from local and continental regions whereas sea-salt aerosol was the major source of PM2.5 from marine source regions.  相似文献   

12.
蔡敏  严明良  包云轩 《气象科学》2018,38(5):648-658
为了探明PM_(2.5)中水溶性无机离子的来源和气象因子对其浓度变化的影响,利用2012年2、5、8和11月苏州市PM_(2.5)中水溶性无机离子浓度和本站气象观测数据,分析了苏州市水溶性无机离子的时间变化特征,解析了当地PM_(2.5)中水溶性无机离子的主要来源,探讨了气象因素对离子组分的影响。结果表明:(1)苏州市PM_(2.5)中水溶性无机离子年均浓度大小依次为:SO_4~(2-)NO_3~-NH_4~+Na~+Cl~-K~+Ca~(2+)Mg~(2+)F~-;SO_4~(2-)、NH_4~+和NO_3~-为PM_(2.5)中最重要的3种水溶性无机离子物种,其总和占PM_(2.5)总质量浓度的50.9%。各离子的季节浓度特征均为冬季最高、夏季最低。(2)通过运用主成分分析法对苏州市PM_(2.5)中水溶性无机离子进行来源分类解析,发现第一类为二次污染源和生物质燃烧,其贡献率为32.84;第二类为道路扬尘及工业排放,其贡献率为19.99%;第三类为海盐污染,其贡献率为18.43%。(3)通过水溶性无机离子与气象条件的相关性分析发现,风向、风速和温度与水溶性无机离子浓度的相关性较显著,这三者是颗粒物浓度变化的主要影响因子。(4)利用HYSPLIT后向轨迹模式对外来污染物进入苏州市的轨迹进行聚类分析后发现:因受季风气候影响,苏州市外来污染物的输入路径存在明显的季节性变化特征,其中夏半年输送主径源自海上,冬半年主径源自内陆。  相似文献   

13.
本文利用气体组分及大气气溶胶在线监测系统(MARGA ADI 2080)观测武汉市2018年1月9—26日大气气溶胶中的8种水溶性离子(NH+4、NO-3、SO2-4、Cl-、K+、Ca2+、Na+和Mg2+),结合气象要素数据,使用主成分分析(PCA)、正定矩阵因子分析法(PMF)、HYSPLIT后向轨迹模式、潜在源区贡献(PSCF)和浓度权重轨迹(CWT),对霾污染过程中水溶性离子进行了全面的来源解析,探究了霾不同阶段下来源差异和空间分布特征。结果表明:(1)本次霾污染中的8种水溶性离子和4种污染气体,PCA解析出的源和占比分别为二次源和燃煤源的混合源(41.28%)、工业排放和土壤扬尘混合源(27.73%)和机动车排放源(9.63%),PMF解析出的源和占比分别为燃煤与土壤扬尘混合源(18.57%)、机动车排放源(20.74%)、二次源(18.30%)、光化学污染源(22.24%)和燃煤源(20.15%)。(2)霾在不同阶段下水溶性离子和4种污染气体的来源存在差异,在清洁天和霾消散阶段,光化学的贡献最高,占比分别为31.42%和36.07%;在霾发生阶段燃煤与土壤扬尘源的贡献最高,其贡献为40.94%;在霾发展阶段,最大的控制源为二次源,贡献占比为37.51%。(3)此次武汉市霾污染中PM2.5浓度和NH+4、NO-3和SO2-4的潜在源区为皖豫鄂三省和赣湘鄂三省交界处。霾污染中PM2.5的主要影响范围是武汉市南部和北部省份,NO-3、NH+4和SO2-4的主要影响区域为武汉市东北方向的城市、湖南省和江西省。  相似文献   

14.
Long-term measurements of ambient particulate matter less than 2.5 μm in diameter (PM2.5) and its chemical compositions were performed at a rural site in Korea from December 2005 to August 2009. The average PM2.5 concentration was 31 μg m−3 for the whole sampling period, and showed a slightly downward annual trend. The major components of PM2.5 were organic carbon, SO42−, NO3, and NH4+, which accounted for 55 % of total PM2.5 mass on average. For the top 10 % of PM2.5 samples, anionic constituents and trace elements clearly increased while carbonaceous constituents and NH4+ remained relatively constant. Both Asian dust and fog events clearly increased PM2.5 concentrations, but affected its chemical composition differently. While trace elements significantly increased during Asian dust events, NO3, NH4+ and Cl were dramatically enhanced during fog events due to the formation of saturated or supersaturated salt solution. The back-trajectory based model, PSCF (Potential Source Contribution Function) identified the major industrial areas in Eastern China as the possible source areas for the high PM2.5 concentrations at the sampling site. Using factor analysis, soil, combustion processes, non-metal manufacture, and secondary PM2.5 sources accounted for 77 % of the total explained variance.  相似文献   

15.

In this study we present the seasonal chemical characteristics and potential sources of PM10 at an urban location of Delhi, India during 2010?2019. The concentrations of carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and water insoluble organic carbon (WIOC)] and elements (Al, Fe, Ti, Cu, Zn, Mn, Pb, Cr, F, Cl, Br, P, S, K, As, Na, Mg, Ca, B, Ni, Mo, V, Sr, Zr and Rb) in PM10 were estimated to explore their possible sources. The annual average concentration (2010–2019) of PM10 was computed as 227?±?97 µg m?3 with a range of 34?734 µg m?3. The total carbonaceous aerosols in PM10 was accounted for 22.5% of PM10 mass concentration, whereas elements contribution to PM10 was estimated to be 17% of PM10. The statistical analysis of OC vs. EC and OC vs. WSOC of PM10 reveals their common sources (biomass burning and/or fossil fuel combustion) during all the seasons. Enrichment factors (EFs) of the elements and the relationship of Al with other crustal metals (Fe, Ca, Mg and Ti) of PM10 indicates the abundance of mineral dust over Delhi. Principal component analysis (PCA) extracted the five major sources [industrial emission (IE), biomass burning?+?fossil fuel combustion (BB?+?FFC), soil dust, vehicular emissions (VE) and sodium and magnesium salts (SMS)] of PM10 in Delhi, India. Back trajectory and cluster analysis of airmass parcel indicate that the pollutants approaching to Delhi are mainly from Pakistan, IGP region, Arabian Sea and Bay of Bengal.

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16.
A study has been carried out on water soluble ions, trace elements, as well as PM2.5 and PM2.5–10 elemental and organic carbon samples collected daily from Central Taiwan over a one year period in 2005. A source apportionment study was performed, employing a Gaussian trajectory transfer coefficient model (GTx) to the results from 141 sets of PM2.5 and PM2.5–10 samples. Two different types of PM10 episodes, local pollution (LOP) and Asian dust storm (ADS) were observed in this study. The results revealed that relative high concentrations of secondary aerosols (NO3, SO42− and NH4+) and the elements Cu, Zn, Cd, Pb and As were observed in PM2.5 during LOP periods. However, sea salt species (Na+ and Cl) and crustal elements (e.g., Al, Fe, Mg, K, Ca and Ti) of PM2.5–10 showed a sharp increase during ADS periods. Anthropogenic source metals, Cu, Zn, Cd, Pb and As, as well as coarse nitrate also increased with ADS episodes. Moreover, reconstruction of aerosol compositions revealed that soil of PM2.5–10 elevated approximately 12–14% in ADS periods than LOP and Clear periods. A significantly high ratio of non-sea salt sulfate to elemental carbon (NSS-SO42−/EC) of PM2.5–10 during ADS periods was associated with higher concentrations of non-sea-salt sulfates from the industrial regions of China. Source apportionment analysis showed that 39% of PM10, 25% of PM2.5, 50% of PM2.5–10, 42% of sulfate and 30% of nitrate were attributable to the long range transport during ADS periods, respectively.  相似文献   

17.
PM2.5 aerosols were sampled in urban Chengdu from April 2009 to January 2010, and their chemical compositions were characterized in detail for elements, water soluble inorganic ions, and carbonaceous matter. The annual average of PM2.5 was 165g m-3, which is generally higher than measurements in other Chinese cities, suggesting serious particulate pollution issues in the city. Water soluble ions contributed 43.5% to the annual total PM2.5 mass, carbonaceous aerosols including elemental carbon and organic carbon contributed 32.0%, and trace elements contributed 13.8%. Distinct daily and seasonal variations were observed in the mass concentrations of PM2.5 and its components, reflecting the seasonal variations of different anthropogenic and natural sources. Weakly acidic to neutral particles were found for PM2.5. Major sources of PM2.5 identified from source apportionment analysis included coal combustion, traffic exhaust, biomass burning, soil dust, and construction dust emissions. The low nitrate: sulfate ratio suggested that stationary emissions were more important than vehicle emissions. The reconstructed masses of ammonium sulfate, ammonium nitrate, particulate carbonaceous matter, and fine soil accounted for 79% of the total measured PM2.5 mass; they also accounted for 92% of the total measured particle scattering.  相似文献   

18.
The main objective of this study is to investigate the chemical characteristics of biomass burning aerosol and its impact on regional air quality during an agricultural waste burning period in early summer in the rural areas of Korea. A 12-h integrated intensive sampling of biomass burning aerosol in the fine and coarse modes was conducted on 2–20 June 2003 in Gwangju, Korea. The collected samples were analyzed for concentrations of mass, ionic, elemental, and carbonaceous species. Average concentrations of fine and coarse mass were measured to be 67.9 and 18.7 μg m− 3 during the biomass burning period, 41.9 and 18.8 μg m− 3 during the haze period, and 35.6 and 13.3 μg m− 3 during the normal period, respectively. An exceptionally high PM2.5 concentration of 110.3 μg m− 3 with a PM2.5/PM10 ratio of 0.79 was observed on 6 June 2003 during the biomass burning period. The potassium ratio method was used to identify biomass burning samples. The average ratio of potassium in the fine mode to the coarse mode (FK/CK) was 23.8 during the biomass burning period, 6.0 during the haze period, and 4.7 during the normal period, respectively. A FK/CK ratio above 9.2 was considered a criterion for biomass burning event in this study. Particulate matter from the open field burning of agricultural waste has an adverse impact on visibility, human health, and regional air quality.  相似文献   

19.
南京市主城区大气颗粒物来源探讨   总被引:9,自引:0,他引:9       下载免费PDF全文
在2005-05-03——05-27期间,用Anderson九级采样器在南京市两个采样点采集大气气溶胶样品,同时进行了部分排放源的采集。用X射线—荧光光谱仪(XRF)分析得到气样及源样中PM10的化学成分,分析了南京市大气气溶胶的元素质量谱分布,进行了PM10的富集因子分析,并应用化学质量平衡法(CMB)计算各类源对气溶胶PM10的贡献。结果表明,各类污染源对南京市气溶胶PM10的贡献率分别为:建筑尘(35.45%)、煤烟尘(22.13%)、土壤尘(20.27%)、硫酸盐(5.43%)、汽车尘(4.61%)、海盐(1.91%)、冶炼尘(1.69%)、其它源(8.51%)。文中还结合了南京市TSP和PM2.5的来源解析结果,分析了南京市不同粒径气溶胶颗粒物的污染特征。  相似文献   

20.

This study presents the chemical composition (carbonaceous and nitrogenous components) of aerosols (PM2.5 and PM10) along with stable isotopic composition (δ13C and δ15N) collected during winter and the summer months of 2015–16 to explore the possible sources of aerosols in megacity Delhi, India. The mean concentrations (mean?±?standard deviation at 1σ) of PM2.5 and PM10 were 223?±?69 µg m?3 and 328?±?65 µg m?3, respectively during winter season whereas the mean concentrations of PM2.5 and PM10 were 147?±?22 µg m?3 and 236?±?61 µg m?3, respectively during summer season. The mean value of δ13C (range: ??26.4 to ??23.4‰) and δ15N (range: 3.3 to 14.4‰) of PM2.5 were ??25.3?±?0.5‰ and 8.9?±?2.1‰, respectively during winter season whereas the mean value of δ13C (range: ??26.7 to ??25.3‰) and δ15N (range: 2.8 to 11.5‰) of PM2.5 were ??26.1?±?0.4‰ and 6.4?±?2.5‰, respectively during the summer season. Comparison of stable C and N isotopic fingerprints of major identical sources suggested that major portion of PM2.5 and PM10 at Delhi were mainly from fossil fuel combustion (FFC), biomass burning (BB) (C-3 and C-4 type vegitation), secondary aerosols (SAs) and road dust (SD). The correlation analysis of δ13C with other C (OC, TC, OC/EC and OC/WSOC) components and δ15N with other N components (TN, NH4+ and NO3?) are also support the source identification of isotopic signatures.

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