Source apportionment of PM10 in Delhi, India using PCA/APCS, UNMIX and PMF

被引:124
|
作者
Jain, Srishti [1 ,2 ]
Sharma, S. K. [1 ,2 ]
Mandal, T. K. [1 ,2 ]
Saxena, Mohit [1 ]
机构
[1] CSIR, Natl Phys Lab, Environm Sci & Biomed Metrol Div, Dr KS Krishnan Rd, New Delhi 110012, India
[2] Acad Sci & Innovat Res AcSIR, CSIR Natl Phys Lab Campus, New Delhi 110012, India
关键词
Receptor model; PCA/APCS; UNMIX; PMF; Source apportionment; POSITIVE MATRIX FACTORIZATION; SUSPENDED PARTICULATE MATTER; BALANCE SOURCE APPORTIONMENT; PARTICLE-SIZE DISTRIBUTION; VOLATILE ORGANIC-COMPOUNDS; COMBINING FACTOR-ANALYSIS; CHEMICAL-CHARACTERIZATION; RECEPTOR MODELS; AMBIENT AIR; ELEMENTAL CARBON;
D O I
10.1016/j.partic.2017.05.009
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Source apportionment of particulate matter (PM10) measurements taken in Delhi, India between January 2013 and June 2014 was carried out using two receptor models, principal component analysis with absolute principal component scores (PCA/APCS) and UNMIX. The results were compared with previous estimates generated using the positive matrix factorization (PMF) receptor model to investigate each model's source-apportioning capability. All models used the P-10 chemical composition (organic carbon (OC), elemental carbon (EC), water soluble inorganic ions (WSIC), and trace elements) for source apportionment. The average PM10 concentration during the study period was 249.7 +/- 103.9 mu g/m(3) (range: 61.4-584.8 mu g/m(3)). The UNMIX model resolved five sources (soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), a mixed source of biomass burning (BB) and sea salt (SS), and industrial emissions (IE)). The PCA/APCS model also resolved five sources, two of which also included mixed sources (SD, VE, SD+SS, (SA+BB+SS) and 1E). The PMF analysis differentiated seven individual sources (SD, VE, SA, BB, SS, IE, and fossil fuel combustion (FFC)). All models identified the main sources contributing to PM10 emissions and reconfirmed that VE, SA, BB, and SD were the dominant contributors in Delhi. (C) 2017 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:107 / 118
页数:12
相关论文
共 50 条
  • [21] Atmospheric aerosol chemistry and source apportionment of PM10 using stable carbon isotopes and PMF modelling during fireworks over Hyderabad, southern India
    Attri, Pradeep
    Mani, Devleena
    Reddy, D. V.
    Kumar, Devender
    Sarkar, Siddhartha
    Kumar, Sanjeev
    Hegde, Prashant
    [J]. HELIYON, 2024, 10 (05)
  • [22] Source identification and health risk assessment of PM2.5 in urban districts of Hanoi using PCA/APCS and UNMIX
    Bui, Thi Hieu
    Nguyen, Thi Phuong Mai
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2024, 31 (08) : 11815 - 11831
  • [23] Source identification and health risk assessment of PM2.5 in urban districts of Hanoi using PCA/APCS and UNMIX
    Thi Hieu Bui
    Thi Phuong Mai Nguyen
    [J]. Environmental Science and Pollution Research, 2024, 31 : 11815 - 11831
  • [24] PM10 source identification using the trajectory based potential source apportionment (TraPSA) toolkit at Kochi, India
    Shanavas, Afifa Kombanezhathu
    Zhou, Chuanlong
    Menon, Ratish
    Hopke, Philip K.
    [J]. ATMOSPHERIC POLLUTION RESEARCH, 2020, 11 (09) : 1535 - 1542
  • [25] Source identification and apportionment of PM2.5 and PM2.5-10 in iron and steel scrap smelting factory environment using PMF, PCFA and UNMIX receptor models
    Ogundele, Lasun T.
    Owoade, Oyediran K.
    Olise, Felix S.
    Hopke, Philip K.
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2016, 188 (10)
  • [26] Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India
    Choudhary, Nikki
    Rai, Akansha
    Kuniyal, Jagdish Chandra
    Srivastava, Priyanka
    Lata, Renu
    Dutta, Monami
    Ghosh, Abhinandan
    Dey, Supriya
    Sarkar, Sayantan
    Gupta, Sakshi
    Chaudhary, Sheetal
    Thakur, Isha
    Bawari, Archana
    Naja, Manish
    Vijayan, Narayanasamy
    Chatterjee, Abhijit
    Mandal, Tuhin Kumar
    Sharma, Sudhir Kumar
    Kotnala, Ravindra Kumar
    [J]. ATMOSPHERE, 2023, 14 (05)
  • [27] Groundwater Pollution Source Identification and Apportionment Using PMF and PCA-APCS-MLR Receptor Models in Tongchuan City, China
    Li, Wenqu
    Wu, Jianhua
    Zhou, Changjing
    Nsabimana, Abel
    [J]. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY, 2021, 81 (03) : 397 - 413
  • [28] Source apportionment of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH) associated to airborne PM10 by a PMF model
    M. S. Callén
    A. Iturmendi
    J. M. López
    A. M. Mastral
    [J]. Environmental Science and Pollution Research, 2014, 21 : 2064 - 2076
  • [29] Source apportionment of PM10 at a traffic station in Dresden
    Gerwig, H
    Bittner, H
    Brüggemann, E
    Gnauk, T
    Herrmann, H
    Löschau, G
    Müller, K
    [J]. GEFAHRSTOFFE REINHALTUNG DER LUFT, 2006, 66 (04): : 175 - 180
  • [30] Source apportionment of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH) associated to airborne PM10 by a PMF model
    Callen, M. S.
    Iturmendi, A.
    Lopez, J. M.
    Mastral, A. M.
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2014, 21 (03) : 2064 - 2076