A systematic approach for the comparison of PM10, PM2.5, and PM1 mass concentrations of characteristic environmental sites

  • Antonio SperanzaEmail author
  • Rosa Caggiano
  • Vito Summa


This study explores the use of a systematic approach in the comparison of simultaneous measurements of PM10, PM2.5, and PM1 mass concentrations using Aitchison geometry. Three case studies in three different Asian cities where the PM coarse, fine, and ultrafine size fraction prevail were investigated and the data was displayed using a dedicated triangular diagram. Simultaneous size-segregated PM measurements, for each case study, were assessed in terms of PM ratios and PM10 levels and were compared to similar measurements reported in literature. Non-central chi-squared distribution quantiles, for each case study, were evaluated and used to investigate the degree of similarity between simultaneous size-segregated PM ratios. Likewise, a comparative number k was used to show the proportion between PM10 levels. The issues relating to the location of the simultaneous size-segregated PM ratios on the triangular diagram were examined and the effects of the non-centrality parameter λ on PM comparison were indicated. The results show that the proposed systematic approach can estimate an explorative quantile (i.e., 2.5%) within which the simultaneous size-segregated PM measurements from one site can be compared with simultaneous size-segregated PM measurements from other sites reported in literature highlighting the existence of possible similarities or correspondences in the kind of sources influencing the PM.


Compositional data analysis Simultaneous size-segregated PM measurements PM ratios Quantile 


Supplementary material

10661_2019_7828_MOESM1_ESM.doc (46 kb)
ESM 1 (DOC 46 kb)


  1. Aitchison, J. (1982). The statistical analysis of compositional data (with discussion). Journal of the Royal Statistical Society: Series B (Statistical Methodology), 44(2), 139–177.Google Scholar
  2. Aitchison, J. (1986). The statistical analysis of compositional data. London: Chapman and Hall 416p.CrossRefGoogle Scholar
  3. Aitchison, J. (2005) A concise guide to compositional data analysis 2nd Compositional Data Analysis Workshop — CoDaWork'05, Universitat de Girona, Girona (2005)
  4. Alastuey, A., Querol, X., Rodriguez, S., Plana, F., Lopez-Soler, A., Ruiz, C., & Mantilla, E. (2004). Monitoring of atmospheric particulate matter around sources of secondary inorganic aerosol. Atmospheric Environment, 38(30), 4979–4992.CrossRefGoogle Scholar
  5. Alastuey, A., Querol, X., Castillo, S., Escudero, M., Avila, A., Cuevas, E., et al. (2005). Characterisation of TSP and PM2. 5 at Izaña and Sta. Cruz de Tenerife (Canary Islands, Spain) during a Saharan dust episode (July 2002). Atmospheric Environment, 39(26), 4715–4728.CrossRefGoogle Scholar
  6. Alastuey, A., Querol, X., Plana, F., Viana, M., Ruiz, C. R., Campa, A. S. D. L., et al. (2006). Identification and chemical characterization of industrial particulate matter sources in Southwest Spain. Journal of the Air & Waste Management Association, 56(7), 993–1006.CrossRefGoogle Scholar
  7. Alghamdi, M. A., Almazroui, M., Shamy, M., Redal, M. A., Alkhalaf, A. K., Hussein, M. A., & Khoder, M. I. (2015). Characterization and elemental composition of atmospheric aerosol loads during springtime dust storm in western Saudi Arabia. Aerosol and Air Quality Research, 15(2), 440–453.CrossRefGoogle Scholar
  8. Amato, F., Pandolfi, M., Escrig, A., Querol, X., Alastuey, A., Pey, J., et al. (2009). Quantifying road dust resuspension in urban environment by multilinear engine: a comparison with PMF2. Atmospheric Environment, 43(17), 2770–2780.CrossRefGoogle Scholar
  9. Anderson, J. O., Thundiyil, J. G., & Stolbach, A. (2012). Clearing the air: a review of the effects of particulate matter air pollution on human health. Journal of Medical Toxicology, 8(2), 166–175.CrossRefGoogle Scholar
  10. Artiñano, B., Salvador, P., Alonso, D. G., Querol, X., & Alastuey, A. (2004). Influence of traffic on the PM 10 and PM 2.5 urban aerosol fractions in Madrid (Spain). Sci. Total Environ., 334, 111–123.CrossRefGoogle Scholar
  11. Bathmanabhan, S., & Madanayak, S. N. S. (2010). Analysis and interpretation of particulate matter–PM 10, PM 2.5 and PM 1 emissions from the heterogeneous traffic near an urban roadway. Atmospheric Pollution Research, 1(3), 184–194.CrossRefGoogle Scholar
  12. Begam, G. R., Vachaspati, C. V., Ahammed, Y. N., Kumar, K. R., Reddy, R. R., Sharma, S. K., et al. (2017). Seasonal characteristics of water-soluble inorganic ions and carbonaceous aerosols in total suspended particulate matter at a rural semi-arid site, Kadapa (India). Environemental Science and Pollution Research, 24(2), 1719–1734.CrossRefGoogle Scholar
  13. Beh, B. C., Tan, F., Tan, C. H., Syahreza, S., Mat Jafri, M. Z., & Lim, H. S. (2013). PM10, PM2. 5 and PM1 distribution in Penang Island, Malaysia. In: AIP Conference Proceedings (Vol. 1528, no. 1, pp. 146-150). AIP.Google Scholar
  14. Buccianti, A., Pawlowsky-Glahn, V., Barceló-Vidal, C., Jarauta-Bragulat, E. (1999). Visualization and modeling of natural trends in ternary diagrams: a geochemical case study. In Proceedings of IAMG (Vol. 99, pp. 139–144).Google Scholar
  15. Cabada, J. C., Rees, S., Takahama, S., Khlystov, A., Pandis, S. N., Davidson, C. I., & Robinson, A. L. (2004). Mass size distributions and size resolved chemical composition of fine particulate matter at the Pittsburgh supersite. Atmospheric Environment, 38(20), 3127–3141.CrossRefGoogle Scholar
  16. Caggiano, R., Macchiato, M., & Trippetta, S. (2010). Levels, chemical composition and sources of fine aerosol particles (PM1) in an area of the Mediterranean basin. Sci. Total Environ., 408(4), 884–895.CrossRefGoogle Scholar
  17. Calvello, M., Caggiano, R., Esposito, F., Lettino, A., Sabia, S., Summa, V., & Pavese, G. (2017). IMAA (integrated measurements of aerosol in Agri valley) campaign: multi-instrumental observations at the largest European oil/gas pre-treatment plant area. Atmospheric Environment, 169, 297–306.CrossRefGoogle Scholar
  18. Cheng, Y., Ho, K. F., Lee, S. C., & Law, S. W. (2006). Seasonal and diurnal variations of PM1. 0, PM2. 5 and PM10 in the roadside environment of Hong Kong. China Particuology, 4(6), 312–315.CrossRefGoogle Scholar
  19. Cheung, H. C., Chou, C. K., Huang, W. R., & Tsai, C. Y. (2013). Characterization of ultrafine particle number concentration and new particle formation in an urban environment of Taipei, Taiwan. Atmospheric Chemistry and Physics, 13(17), 8935–8946.CrossRefGoogle Scholar
  20. Chiari, M., Del Carmine, P., Lucarelli, F., Marcazzan, G., Nava, S., Paperetti, L., et al. (2004). Atmospheric aerosol characterisation by ion beam analysis techniques: recent improvements at the Van de Graaff laboratory in Florence. Nuclear Instruments and Methods in Physics Research B, 219, 166–170.CrossRefGoogle Scholar
  21. Chiari, M., Lucarelli, F., Mazzei, F., Nava, S., Paperetti, L., Prati, P., et al. (2005). Characterization of airborne particulate matter in an industrial district near Florence by PIXE and PESA. X-Ray Spectrometry, 34(4), 323–329.CrossRefGoogle Scholar
  22. Choi, H., & Choi, D. S. (2008). Concentrations of PM 10, PM 2.5, and PM 1 influenced by atmospheric circulation and atmospheric boundary layer in the Korean mountainous coast during a dust storm. Atmospheric Research, 89(4), 330–337.CrossRefGoogle Scholar
  23. Claiborn, C. S., Finn, D., Larson, T. V., & Koenig, J. Q. (2000). Windblown dust contributes to high PM25 concentrations. Journal of the Air & Waste Management Association, 50(8), 1440–1445.CrossRefGoogle Scholar
  24. Colbeck, I. (Ed.). (2008). Environmental chemistry of aerosols. Oxford: Blackwell Publishing Ltd.Google Scholar
  25. Colbeck, I., Nasir, Z. A., Ahmad, S., & Ali, Z. (2011). Exposure to PM10, PM2.5, PM1 and carbon monoxide on roads in Lahore, Pakistan. Aerosol and Air Quality Research, 11, 689–695.CrossRefGoogle Scholar
  26. Deng, X., Tie, X., Zhou, X., Wu, D., Zhong, L., Tan, H., et al. (2008). Effects of Southeast Asia biomass burning on aerosols and ozone concentrations over the Pearl River Delta (PRD) region. Atmospheric Environment, 42(36), 8493–8501.CrossRefGoogle Scholar
  27. Egozcue, J. J., Pawlowsky-Glahn, V., Mateu-Figueras, G., & Barceló-Vidal, C. (2003). Isometric logratio transformations for compositional data analysis. Mathematical Geology, 35(3), 279–300.CrossRefGoogle Scholar
  28. Filzmoser, P., & Hron, K. (2008). Outlier detection for compositional data using robust methods. Mathematical Geoscience, 40(3), 233–248.CrossRefGoogle Scholar
  29. Filzmoser, P., Ruiz-Gazen, A., & Thomas-Agnan, C. (2014). Identification of local multivariate outliers. Statistical Papers, 55(1), 29–47.CrossRefGoogle Scholar
  30. Galindo, N., Varea, M., Gil-Moltó, J., Yubero, E., & Nicolás, J. (2011). The influence of meteorology on particulate matter concentrations at an urban Mediterranean location. Water, Air, and Soil Pollution, 215(1–4), 365–372.CrossRefGoogle Scholar
  31. Gerasopoulos, E., Koulouri, E., Kalivitis, N., Kouvarakis, G., Saarikoski, S., Mäkelä, T., et al. (2007). Size-segregated mass distributions of aerosols over eastern Mediterranean: seasonal variability and comparison with AERONET columnar size-distributions. Atmospheric Chemistry and Physics, 7(10), 2551–2561.CrossRefGoogle Scholar
  32. Giugliano, M., Lonati, G., Butelli, P., Romele, L., Tardivo, R., & Grosso, M. (2005). Fine particulate (PM2. 5–PM1) at urban sites with different traffic exposure. Atmospheric Environment, 39(13), 2421–2431.CrossRefGoogle Scholar
  33. Godec, R., Čačković, M., Šega, K., & Bešlić, I. (2012). Winter mass concentrations of carbon species in PM10, PM2. 5 and PM1 in Zagreb air, Croatia. Bulletin of Environmental Contamination and Toxicology, 89(5), 1087–1090.CrossRefGoogle Scholar
  34. Gomišček, B., Hauck, H., Stopper, S., & Preining, O. (2004). Spatial and temporal variations of PM 1, PM 2.5, PM 10 and particle number concentration during the AUPHEP—Project. Atmospheric Environment, 38(24), 3917–3934.CrossRefGoogle Scholar
  35. Gong, W., Zhang, T., Zhu, Z., Ma, Y., Ma, X., & Wang, W. (2015). Characteristics of PM1. 0, PM2. 5, and PM10, and their relation to black carbon in Wuhan, Central China. Atmosphere, 6(9), 1377–1387.CrossRefGoogle Scholar
  36. Graham, D. J., & Midgley, N. G. (2000). Technical communication-graphical representation of particle shape using triangular diagrams: an excel spreadsheet method. Earth Surface Processes and Landforms, 25(13), 1473–1478.CrossRefGoogle Scholar
  37. Guo, L. C., Bao, L. J., She, J. W., & Zeng, E. Y. (2014). Significance of wet deposition to removal of atmospheric particulate matter and polycyclic aromatic hydrocarbons: a case study in Guangzhou, China. Atmospheric Environment, 83, 136–144.CrossRefGoogle Scholar
  38. Halek, F., Keyanpour, M., Pirmoradi, A., & Kavousi, A. (2010). Estimation of urban suspended particulate air pollution concentration. International Journal of Environmental Research., 4(1), 161–168.Google Scholar
  39. Haller, L., Claiborn, C., Larson, T., Koenig, J., Norris, G., & Edgar, R. (1999). Airborne particulate matter size distributions in an arid urban area. Journal of the Air & Waste Management Association, 49(2), 161–168.CrossRefGoogle Scholar
  40. Harrison, R. M., Shi, J. P., Xi, S., Khan, A., Mark, D., Kinnersley, R., & Yin, J. (2000). Measurement of number, mass and size distribution of particles in the atmosphere. Philosophical Transactions of the Royal Society A, 358(1775), 2567–2580.CrossRefGoogle Scholar
  41. Harrison, S. P., Kohfeld, K. E., Roelandt, C., & Claquin, T. (2001). The role of dust in climate changes today, at the last glacial maximum and in the future. Earth Science Reviews, 54(1), 43–80.CrossRefGoogle Scholar
  42. Hassanvand, M. S., Naddafi, K., Faridi, S., Arhami, M., Nabizadeh, R., Sowlat, M. H., et al. (2014). Indoor/outdoor relationships of PM 10, PM 2.5, and PM 1 mass concentrations and their water-soluble ions in a retirement home and a school dormitory. Atmospheric Environment, 82, 375–382.CrossRefGoogle Scholar
  43. He, J., Gong, S., Yu, Y., Yu, L., Wu, L., Mao, H., et al. (2017). Air pollution characteristics and their relation to meteorological conditions during 2014–2015 in major Chinese cities. Environmental Pollution, 223, 484–496.CrossRefGoogle Scholar
  44. Heyder, J. (2004). Deposition of inhaled particles in the human respiratory tract and consequences for regional targeting in respiratory drug delivery. Proceedings of the American Thoracic Society, 1, 315–320.CrossRefGoogle Scholar
  45. Hieu, N. T., & Lee, B. K. (2010). Characteristics of particulate matter and metals in the ambient air from a residential area in the largest industrial city in Korea. Atmospheric Research, 98(2), 526–537.CrossRefGoogle Scholar
  46. IPCC. (2013). Summary for policymakers. In T. F. Stocker, D. Qin, G. K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, & P. M. Midgley (Eds.), Climate change (2013): The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change (p. 1535). Cambridge: Cambridge University Press.Google Scholar
  47. Kelly, F. J., & Fussell, J. C. (2012). Size, source and chemical composition as determinants of toxicity attributable to ambient particulate matter. Atmospheric Environment, 60, 504–526.CrossRefGoogle Scholar
  48. Keywood, M. D., Ayers, G. P., Gras, J. L., Gillett, R. W., & Cohen, D. D. (1999). Relationships between size segregated mass concentration data and ultrafine particle number concentrations in urban areas. Atmospheric Environment, 33(18), 2907–2913.CrossRefGoogle Scholar
  49. Khamdan, S. A. A., Al Madany, I. M., & Buhussain, E. (2009). Temporal and spatial variations of the quality of ambient air in the Kingdom of Bahrain during 2007. Environmental Monitoring and Assessment, 154(1–4), 241.CrossRefGoogle Scholar
  50. Klejnowski, K., Pastuszka, J. S., Rogula-Kozłowska, W., Talik, E., & Krasa, A. (2012). Mass size distribution and chemical composition of the surface layer of summer and winter airborne particles in Zabrze, Poland. Bulletin of Environmental Contamination and Toxicology., 88(2), 255–259.CrossRefGoogle Scholar
  51. Laakso, L., Hussein, T., Aarnio, P., Komppula, M., Hiltunen, V., Viisanen, Y., & Kulmala, M. (2003). Diurnal and annual characteristics of particle mass and number concentrations in urban, rural and Arctic environments in Finland. Atmospheric Environment, 37(19), 2629–2641.CrossRefGoogle Scholar
  52. Lepeule, J., Laden, F., Dockery, D., & Schwartz, J. (2012). Chronic exposure to fine particles and mortality: an extended follow-up of the Harvard Six Cities study from 1974 to 2009. Environmental Health Perspectives, 120(7), 965.CrossRefGoogle Scholar
  53. Li, C. S., & Lin, C. H. (2002). PM 1/PM 2.5/PM 10 characteristics in the urban atmosphere of Taipei. Aerosol Science and Technology, 36(4), 469–473.CrossRefGoogle Scholar
  54. Li, Y., Chen, Q., Zhao, H., Wang, L., & Tao, R. (2015). Variations in PM10, PM2. 5 and PM1. 0 in an urban area of the Sichuan Basin and their relation to meteorological factors. Atmosphere, 6(1), 150–163.CrossRefGoogle Scholar
  55. Lim, S., Lee, M., Lee, G., Kim, S., Yoon, S., & Kang, K. (2012). Ionic and carbonaceous compositions of PM 10, PM 2.5 and PM 1.0 at Gosan ABC superstation and their ratios as source signature. Atmospheric Chemistry and Physics, 12(4), 2007–2024.CrossRefGoogle Scholar
  56. Lundgren, D. A., Hlaing, D. N., Rich, T. A., & Marple, V. A. (1996). PM10/PM2. 5/PM1 data from a trichotomous sampler. Aerosol Science and Technology, 25(3), 353–357.CrossRefGoogle Scholar
  57. Maechler, M., Rousseeuw, P., Croux, C., Todorov, V., Ruckstuhl, A., Salibian-Barrera, M., Verbeke, T., Koller, M., Conceicao, E. L. T., and di Palma M. A. (2016). Robustbase: basic robust statistics R package version 0.92-7. URL
  58. Makkonen, U., Hellén, H., Anttila, P., & Ferm, M. (2010). Size distribution and chemical composition of airborne particles in South-Eastern Finland during different seasons and wildfire episodes in 2006. Science of the Total Environment., 408(3), 644–651.CrossRefGoogle Scholar
  59. Mandija, F., Bushati, J., Zoga, P., & Vila, F. (2011). Source apportionment of PM10, PM2. 5 and PM1 in the larger city in the North of Albania. Regional Science Inquiry, 3(1), 85–94.Google Scholar
  60. Margiotta, S., Lettino, A., Speranza, A., & Summa, V. (2015). PM 1 geochemical and mineralogical characterization using SEM-EDX to identify particle origin–Agri Valley pilot area (Basilicata, southern Italy). Natural Hazards and Earth System Sciences, 15(7), 1551–1561.CrossRefGoogle Scholar
  61. Massey, D., Kulshrestha, A., Masih, J., & Taneja, A. B. E. J. (2012). Seasonal trends of PM 10, PM 5.0, PM 2.5 & PM 1.0 in indoor and outdoor environments of residential homes located in north-Central India. Building and Environment, 47, 223–231.CrossRefGoogle Scholar
  62. Moreno, T., Querol, X., Alastuey, A., Reche, C., Cusack, M., Amato, F., et al. (2011). Variations in time and space of trace metal aerosol concentrations in urban areas and their surroundings. Atmospheric Chemistry and Physics, 11(17), 9415–9430.CrossRefGoogle Scholar
  63. Osite, A., Viksna, A., Kleperis, J., & Steinberga, I. (2012). Variations of fine and coarse urban atmospheric aerosol concentrations. International Journal of Energy and Environment, 6, 74–82.Google Scholar
  64. Pastuszka, J. S., Rogula-Kozłowska, W., & Zajusz-Zubek, E. (2010). Characterization of PM10 and PM2. 5 and associated heavy metals at the crossroads and urban background site in Zabrze, upper Silesia, Poland, during the smog episodes. Environmental Monitoring and Assessment, 168(1–4), 613–627.CrossRefGoogle Scholar
  65. Pawlowsky-Glahn, V., & Buccianti, A. (2002). Visualization and modeling of sub-populations of compositional data: statistical methods illustrated by means of geochemical data from fumarolic fluids. International Journal of Earth Sciences, 91(2), 357–368.CrossRefGoogle Scholar
  66. Pawlowsky-Glahn, V., & Buccianti, A. (2011). Compositional data analysis: theory and applications. London: Wiley.CrossRefGoogle Scholar
  67. Pawlowsky-Glahn, V., Egozcue, J. J., & Tolosana Delgado, R. (2007). Lecture notes on compositional data analysis.
  68. Pérez, N., Pey, J., Querol, X., Alastuey, A., López, J. M., & Viana, M. (2008). Partitioning of major and trace components in PM 10–PM 2.5–PM 1 at an urban site in southern Europe. Atmospheric Environment, 42(8), 1677–1691.CrossRefGoogle Scholar
  69. Pérez, N., Pey, J., Cusack, M., Reche, C., Querol, X., Alastuey, A., & Viana, M. (2010). Variability of particle number, black carbon, and PM10, PM2. 5, and PM1 levels and speciation: influence of road traffic emissions on urban air quality. Aerosol Science and Technology, 44(7), 487–499.CrossRefGoogle Scholar
  70. Pey, J., Pérez, N., Castillo, S., Viana, M., Moreno, T., Pandolfi, M., et al. (2009). Geochemistry of regional background aerosols in the Western Mediterranean. Atmospheric Research, 94(3), 422–435.CrossRefGoogle Scholar
  71. Pey, J., Querol, X., & Alastuey, A. (2010). Discriminating the regional and urban contributions in the North-Western Mediterranean: PM levels and composition. Atmospheric Environment, 44(13), 1587–1596.CrossRefGoogle Scholar
  72. Pope III, C. A., & Dockery, D. W. (2006). Health effects of fine particulate air pollution: lines that connect. Journal of the Air & Waste Management Association, 56(6), 709–742.CrossRefGoogle Scholar
  73. Prospero, J.M. (2007) African dust: Its large-scale transport over the Atlantic Ocean and its impact on the Mediterranean region. In Regional Climate Variability and its Impacts in The Mediterranean Area (15-38). Springer Netherlands.Google Scholar
  74. Putaud, J. P., Van Dingenen, R., & Raes, F. (2002). Submicron aerosol mass balance at urban and semirural sites in the Milan area (Italy). Journal of Geophysical Research – Atmospheres, 107(D22).Google Scholar
  75. Putaud, J. P., Raes, F., Van Dingenen, R., Brüggemann, E., Facchini, M. C., Decesari, S., et al. (2004). A European aerosol phenomenology—2: chemical characteristics of particulate matter at kerbside, urban, rural and background sites in Europe. Atmospheric Environment, 38(16), 2579–2595.CrossRefGoogle Scholar
  76. Querol, X., Alastuey, A., Rodriguez, S., Plana, F., Ruiz, C. R., Cots, N., et al. (2001). PM10 and PM2. 5 source apportionment in the Barcelona metropolitan area, Catalonia, Spain. Atmospheric Environment, 35(36), 6407–6419.CrossRefGoogle Scholar
  77. Querol, X., Alastuey, A., Ruiz, C. R., Artiñano, B., Hansson, H. C., Harrison, R. M., et al. (2004). Speciation and origin of PM10 and PM2.5 in selected European cities. Atmospheric Environment, 38(38), 6547–6555.CrossRefGoogle Scholar
  78. Querol, X., Pey, J., Minguillón, M. C., Pérez, N., Alastuey, A., Viana, M., et al. (2008). PM speciation and sources in Mexico during the MILAGRO-2006 campaign. Atmospheric Chemistry and Physics, 8(1), 111–128.CrossRefGoogle Scholar
  79. R Development Core Team (2008). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL
  80. Rodríguez, S., Cuevas, E., González, Y., Ramos, R., Romero, P. M., Pérez, N., et al. (2008). Influence of sea breeze circulation and road traffic emissions on the relationship between particle number, black carbon, PM1, PM2. 5 and PM2. 5–10 concentrations in a coastal city. Atmospheric Environment, 42(26), 6523–6534.CrossRefGoogle Scholar
  81. Rogula-Kozłowska, W. (2015). Chemical composition and mass closure of ambient particulate matter at a crossroads and a highway in Katowice, Poland. Environment Protection Engineering, 41(2), 15–29.Google Scholar
  82. Rousseeuw, P. J., & van Driessen, K. (1999). A fast algorithm for the minimum covariance determinant estimator. Technometrics, 41, 212–223.CrossRefGoogle Scholar
  83. Shahsavani, A., Naddafi, K., Haghighifard, N. J., Mesdaghinia, A., Yunesian, M., Nabizadeh, R., & Alimohamadi, M. (2012). The evaluation of PM 10, PM 2.5, and PM 1 concentrations during the middle eastern dust (MED) events in Ahvaz, Iran, from April through September 2010. Journal of Arid Environments, 77, 72–83.CrossRefGoogle Scholar
  84. Sneed, E. D., & Folk, R. L. (1958). Pebbles in the lower Colorado River, Texas a study in particle morphogenesis. Journal of Geology, 66(2), 114–150.CrossRefGoogle Scholar
  85. Speranza, A., Caggiano, R., Margiotta, S., & Trippetta, S. (2014). A novel approach to comparing simultaneous size-segregated particulate matter (PM) concentration ratios by means of a dedicated triangular diagram using the Agri Valley PM measurements as an example. Natural Hazards and Earth System Sciences, 14(10), 2727–2733.CrossRefGoogle Scholar
  86. Speranza, A., Caggiano, R., Margiotta, S., Summa, V., & Trippetta, S. (2016). A clustering approach based on triangular diagram to study the seasonal variability of simultaneous measurements of PM10, PM2. 5 and PM1 mass concentration ratios. Arabian Journal of Geosciences, 9(2), 1–8.CrossRefGoogle Scholar
  87. Speranza, A., Caggiano, R., Pavese, G., & Summa, V. (2018). The study of characteristic environmental sites affected by diverse sources of mineral matter using compositional data analysis. Condensed Matter, 3(2), 16.CrossRefGoogle Scholar
  88. Spindler, G., Müller, K., Brüggemann, E., Gnauk, T., & Herrmann, H. (2004). Long-term size-segregated characterization of PM 10, PM 2.5, and PM 1 at the IfT research station Melpitz downwind of Leipzig (Germany) using high and low-volume filter samplers. Atmospheric Environment, 38(31), 5333–5347.CrossRefGoogle Scholar
  89. Spindler, G., Brüggemann, E., Gnauk, T., Grüner, A., Müller, K., & Herrmann, H. (2010). A four-year size-segregated characterization study of particles PM 10, PM 2.5 and PM 1 depending on air mass origin at Melpitz. Atmospheric Environment, 44(2), 164–173.CrossRefGoogle Scholar
  90. Srivastava, A., Jain, V. K., & Srivastava, A. (2009). SEM-EDX analysis of various sizes aerosols in Delhi India. Environmental Monitoring and Assessment, 150(1–4), 405.CrossRefGoogle Scholar
  91. Sugimoto, N., Shimizu, A., Matsui, I., & Nishikawa, M. (2016). A method for estimating the fraction of mineral dust in particulate matter using PM 2.5-to-PM 10 ratios. Particuology, 28, 114–120.CrossRefGoogle Scholar
  92. Theodosi, C., Grivas, G., Zarmpas, P., Chaloulakou, A., & Mihalopoulos, N. (2011). Mass and chemical composition of size-segregated aerosols (PM 1, PM 2.5, PM 10) over Athens, Greece: Local versus regional sources. Atmospheric Chemistry and Physics, 11(22), 11895–11911.CrossRefGoogle Scholar
  93. Tiwari, S., Chate, D. M., Srivastava, M. K., Safai, P. D., Srivastava, A. K., Bisht, D. S., & Padmanabhamurty, B. (2012). Statistical evaluation of PM10 and distribution of PM1, PM2. 5, and PM10 in ambient air due to extreme fireworks episodes (Deepawali festivals) in megacity Delhi. Natural Hazards, 61(2), 521–531.CrossRefGoogle Scholar
  94. Trippetta, S., Caggiano, R., & Telesca, L. (2013). Analysis of particulate matter in anthropized areas characterized by the presence of crude oil pre-treatment plants: The case study of the Agri Valley (southern Italy). Atmospheric Environment, 77, 105–116.CrossRefGoogle Scholar
  95. Vallius, M. J., Ruuskanen, J., Mirme, A., & Pekkanen, J. (2000). Concentrations and estimated soot content of PM1, PM2. 5, and PM10 in a subarctic urban atmosphere. Environmental Science & Technology, 34(10), 1919–1925.CrossRefGoogle Scholar
  96. Van Dingenen, R., Raes, F., Putaud, J. P., Baltensperger, U., Charron, A., Facchini, M. C., et al. (2004). European aerosol phenomenology-1: physical characteristics of particulate matter at kerbside, urban, rural and background sites in Europe. Atmospheric Environment, 38, 2561–2577.CrossRefGoogle Scholar
  97. Vecchi, R., Marcazzan, G., Valli, G., Ceriani, M., & Antoniazzi, C. (2004). The role of atmospheric dispersion in the seasonal variation of PM1 and PM2. 5 concentration and composition in the urban area of Milan (Italy). Atmospheric Environment, 38(27), 4437–4446.CrossRefGoogle Scholar
  98. Viana, M., Querol, X., Alastuey, A., Gangoiti, G., & Menéndez, M. (2003). PM levels in the Basque Country (northern Spain): analysis of a 5-year data record and interpretation of seasonal variations. Atmospheric Environment, 37(21), 2879–2891.CrossRefGoogle Scholar
  99. Von Eynatten, H., Pawlowsky-Glahn, V., & Egozcue, J. J. (2002). Understanding perturbation on the simplex: A simple method to better visualize and interpret compositional data in ternary diagrams. Mathematical Geology, 34(3), 249–257.CrossRefGoogle Scholar
  100. Wan, J. M., Lin, M., Chan, C. Y., Zhang, Z. S., Engling, G., Wang, X. M., Chan, I. N., & Li, S. Y. (2011). Change of air quality and its impact on atmospheric visibility in Central-Western Pearl River Delta. Environmental Monitoring and Assessment, 172(1–4), 339–351.CrossRefGoogle Scholar
  101. Wang, Y. Q., Zhang, X. Y., Sun, J. Y., Zhang, X. C., Che, H. Z., & Li, Y. (2015). Spatial and temporal variations of the concentrations of PM 10, PM 2.5 and PM 1 in China. Atmospheric Chemistry and Physics, 15(23), 13585–13598.CrossRefGoogle Scholar
  102. WHO (World Health Organization). Regional Office for Europe, & World Health Organization. (2006). Air quality guidelines: global update 2005: particulate matter, ozone, nitrogen dioxide, and sulfur dioxide. World Health Organization.Google Scholar
  103. WHO (World Health Organization). Regional Office for Europe, & World Health Organization. (2012). Health effects of black carbon. World Health Organization.Google Scholar
  104. Wu, Y., Hao, J., Fu, L., Wang, Z., & Tang, U. (2002). Vertical and horizontal profiles of airborne particulate matter near major roads in Macao, China. Atmospheric Environment, 36(31), 4907–4918.CrossRefGoogle Scholar
  105. Yeh, C. F., Lee, C. L., & Brimblecombe, P. (2016). Effects of seasonality and transport route on chemical characteristics of PM2. 5 and PM2. 5-10 in the east Asian Pacific rim region. Aerosol and Air Quality Research In Press.Google Scholar
  106. Yu, J., Guinot, B., Yu, T., Wang, X., & Liu, W. (2005). Seasonal variations of number size distributions and mass concentrations of atmospheric particles in Beijing. Advances in Atmospheric Sciences, 22(3), 401–407.CrossRefGoogle Scholar
  107. Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H., Kannari, A., et al. (2009). Asian emissions in 2006 for the NASA INTEX-B mission. Atmospheric Chemistry and Physics, 9(14), 5131–5153.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.IMAA, Istituto di Metodologie per l’Analisi Ambientale, CNRTito ScaloItaly

Personalised recommendations