Abstract
In this study, we investigated the impact of potential emission sources and transport pathways on annual and seasonal PM10 loadings in an urban area of Belgrade (Serbia). The analyzed dataset comprised PM10 mass concentrations for the period 2003–2015, as well as their chemical composition (organic/elemental carbon, benzo[a]pyrene, As, Cd, Cr, Mn, Ni, Pb, Cl−, Na+, Mg2+, Ca2+, K+, NO3 −, SO4 2−, and NH4 +), meteorological parameters, and concentrations of inorganic gaseous pollutants and soot for the period 2011–2015. The combination of different methods, such as source apportionment (Unmix), ensemble learning method (random forest), and multifractal and inverse multifractal analysis, was utilized in order to obtain a detailed description of the PM10 origin and spatio-temporal distribution and to determine their relationship with other pollutants and meteorological parameters. The contribution of long-range and regional transport was estimated by means of trajectory sector analysis, whereas the hybrid receptor models were applied to identify potential areas of concern.
Similar content being viewed by others
References
Aldabe J, Elustondo D, Santamaría C, Lasheras E, Pandolfi M, Alastuey A et al (2011) Chemical characterisation and source apportionment of PM2. 5 and PM10 at rural, urban and traffic sites in Navarra (North of Spain). Atmos Res 102:191–205
Almeida SM, Pio CA, Freitas MC, Reis MA, Trancoso MA (2005) Source apportionment of fine and coarse particulate matter in a sub-urban area at the Western European Coast. Atmos Environ 39:3127–3138
Ashbaugh LL, Malm WC, Sadeh WZ (1985) A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmos Environ 19:1263–1270
Barmpadimos I, Hueglin C, Keller J, Henne S, Prévôt ASH (2011) Influence of meteorology on PM10 trends and variability in Switzerland from 1991 to 2008. Atmos Chem Phys 11:1813–1835
Bencko V (1997) Health aspects of burning coal with a high arsenic content: the central Slovakia experience. In: Calderon RL, Chappell WR (eds) Abernathy CO. Arsenic, Springer Netherlands, pp 84–92
Buekers J, Stassen K, Panis LI, Hendrickx K, Torfs R (2011) Ten years of research and policy on particulate matter air pollution in hot spot Flanders. Environ Sci Policy 14:347–355
Carslaw DC, Beevers SD (2013) Characterising and understanding emission sources using bivariate polar plots and k-means clustering. Environ Modell Softw 40:325–329
Carslaw DC, Ropkins K (2012) Openair—an R package for air quality data analysis. Environ Modell Softw 27:52–61
Cavalli F, Viana M, Yttri KE, Genberg J, Putaud JP (2010) Toward a standardised thermal-optical protocol for measuring atmospheric organic and elemental carbon: the EUSAAR protocol. Atmos Meas Tech 3:79–89
Cheng Z, Jiang J, Fajardo O, Wang S, Hao J (2013) Characteristics and health impacts of particulate matter pollution in China (2001–2011). Atmos Environ 65:186–194
Department for Environment, Food and Rural Affairs (DEFRA) and Environmental Agency (2002) Contaminants in soil: collation of toxicological data and intake values for humans. Arsenic (R&D Publication), Bristol
Draxler RR, Rolph GD (2014) HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model access via NOAA ARL READY. NOAA Air Resources Laboratory, Silver Spring, http://ready.arl.noaa.gov/HYSPLIT.php
European Environmental Agency (2013) Air quality in Europe—2013 report, Luxembourg, http://www.eea.europa.eu/publications/air-quality-in-europe-2013. Accessed: 21st May, 2015
European Environmental Agency (2014) Air quality in Europe—2014 report, Luxembourg, http://www.eea.europa.eu/publications/air-quality-in-europe-2014. Accessed: 21st May, 2015
Global Data Assimilation System (2015) https://www.ready.noaa.gov/gdas1.php. Accessed: 20th May, 2015.
Hailin W, Zhuang Y, Ying W, Yele S, Hui Y, Zhuang G, Zhengping H (2008) Long-term monitoring and source apportionment of PM 2.5/PM 10 in Beijing, China. J Environ Sci 20:1323–1327
Hasheminassab S, Daher N, Schauer JJ, Sioutas C (2013) Source apportionment and organic compound characterization of ambient ultrafine particulate matter (PM) in the Los Angeles Basin. Atmos Environ 79:529–539
Heal MR, Hibbs LR, Agius RM, Beverland IJ (2005) Total and water-soluble trace metal content of urban background PM 10, PM 2.5 and black smoke in Edinburgh, UK. Atmos Environ 39:1417–1430
Hsu YK, Holsen TM, Hopke PK (2003) Comparison of hybrid receptor models to locate PCB sources in Chicago. Atmos Environ 37:545–562
Hueglin C, Gehrig R, Baltensperger U, Gysel M, Monn C, Vonmont H (2005) Chemical characterisation of PM2. 5, PM10 and coarse particles at urban, near-city and rural sites in Switzerland. Atmos Environ 39:637–651
INRIA, software Fraclab, A fractal analysis toolbox for signal an image processing. http://fraclab.saclay.inria.fr/works/biomedical
Jorba O, Pandolfi M, Spada M, Baldasano JM, Pey J, Alastuey A et al (2013) Overview of the meteorology and transport patterns during the DAURE field campaign and their impact to PM observations. Atmos Environ 77:607–620
Karanasiou A, Diapouli E, Cavalli F, Eleftheriadis K, Viana M, Alastuey A, Querol X, Reche C (2011) On the quantification of atmospheric carbonate carbon by thermal/optical analysis protocols. Atmos Meas Tech 4:2409–19
Khalil MAK, Rasmussen RA (2003) Tracers of wood smoke. Atmos Environ 37:1211–1222
Lee YK, Otkin JA, Greenwald TJ (2014) Evaluating the accuracy of a high-resolution model simulation through comparison with modis observations. J Appl Meteorol Clim 53:1046–1058
Lenschow P, Abraham HJ, Kutzner K, Lutz M, Preuß JD, Reichenbächer W (2001) Some ideas about the sources of PM10. Atmos Environ 35:S23–S33
Liaw A, Wiener M (2002) Classification and regression by random forest. R news 2(3):18–22
Mysliwiec MJ, Kleeman MJ (2002) Source apportionment of secondary airborne particulate matter in a polluted atmosphere. Environ Sci Technol 36:5376–5384
Opentraj (2015) https://cran.r-project.org/web/packages/opentraj/opentraj.pdf. Accessed: 27th May, 2015.
Pacyna JM (1984) Estimation of the atmospheric emissions of trace elements from anthropogenic sources in Europe. Atmos Environ (1967) 18:41–50
Pandolfi M, Gonzalez-Castanedo Y, Alastuey A, Jesus D, Mantilla E, de la Campa AS et al (2011) Source apportionment of PM10 and PM2.5 at multiple sites in the strait of Gibraltar by PMF: impact of shipping emissions. Environ Sci Pollut R 18:260–269
Pérez C, Nickovic S, Baldasano JM, Sicard M, Rocadenbosch F, Cachorro VE (2006) A long Saharan dust event over the western Mediterranean: Lidar, Sun photometer observations, and regional dust modeling. J Geophys Res-Atmos (1984–2012), 111(D15). doi:10.1029/2005JD00657
Perez L, Grize L, Infanger D, Künzli N, Sommer H, Alt GM, Schindler C (2015) Associations of daily levels of PM10 and NO2 with emergency hospital admissions and mortality in Switzerland: trends and missed prevention potential over the last decade. Environ Res 140:554–561
Perišić M, Stojić A, Stojić SS, Šoštarić A, Mijić Z, Rajšić S (2014) Estimation of required PM10 emission source reduction on the basis of a 10-year period data. Air Qual Atmos Health 8(4):379–389
Pinheiro SDLLD, Saldiva PHN, Schwartz J, Zanobetti A (2014) Isolated and synergistic effects of PM10 and average temperature on cardiovascular and respiratory mortality. Rev Saude Publ 48:881–888
Pretty R (2015) TheilSen {openair} Tests for trends using Theil-Sen estimates, http://www.inside-r.org/packages/cran/openair/docs/TheilSen. Accessed: 15th August, 2015
Querol X, Alastuey A, Moreno T, Viana MM, Castillo S, Pey J et al (2008) Spatial and temporal variations in airborne particulate matter (PM 10 and PM 2.5) across Spain 1999–2005. Atmos Environ 42:3964–3979
Rajšić SF, Tasić MD, Novaković VT, Tomašević MN (2004) First assessment of the PM10 and PM2.5 particulate level in the ambient air of Belgrade City. Environ Sci Pollut R 11:158–164
Reljin I, Reljin B, Pavlović I, Rakočević I (2000) Multifractal analysis of gray-scale images. In Electrotechnical Conference, 2000. MELECON 2000. 10th Mediterranean, Vol. 2, IEEE, pp. 490-493.
Rost J, Holst T, Sahn E, Klingner M, Anke K, Ahrens D, Mayer H (2009) Variability of PM10 concentrations dependent on meteorological conditions. Int J Environ Pollut 36:3–18
Ruf T (1999) The Lomb-Scargle periodogram in biological rhythm research: analysis of incomplete and unequally spaced time-series. Biol Rhythm Res 30:178–201
Stojić A, Stojić SS, Šoštarić A, Ilić L, Mijić Z, Rajšić S (2015a) Characterization of VOC sources in an urban area based on PTR-MS measurements and receptor modelling. Environ Sci Pollut R. 22(17):13137–13152
Stojić A, Stojić SS, Mijić Z, Šoštarić A, Rajšić S (2015b) Spatio-temporal distribution of VOC emissions in urban area based on receptor modeling. Atmos Environ 106:71–79
Stull RB (1988) An introduction to boundary layer meteorology. Springer, London
Team RC (2012) R: a language and environment for statistical computing. http://cran.case.edu/web/packages/dplR/vignettes/timeseries-dplR.pdf. Accessed: 10th June, 2015.
Uria-Tellaetxe I, Carslaw DC (2014) Conditional bivariate probability function for source identification. Environ Modell Softw 59:1–9
USEPA (2007) EPA Unmix 6.0 fundamentals and user guide. USEPA Office of Research and Development, http://archive.epa.gov/heasd/documents/web/pdf/unmix-6-user-manual.pdf. Accessed: 1st August, 2015
Véhel JL (1998) Introduction to the multifractal analysis of images. Fractal Image Encoding and Analysis 159:299–341
Wang YH, Liu ZR, Zhang JK, Hu B, Ji DS, Yu YC, Wang YS (2015) Aerosol physicochemical properties and implications for visibility during an intense haze episode during winter in Beijing. Atmos Chem Phys 15:3205–3215
Wang YQ (2014) MeteoInfo: GIS software for meteorological data visualization and analysis. Meteorol Appl 21:360–368
WHO (2005) Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide global update 2005 summary of risk assessment. http://www.who.int/mediacentre/factsheets/fs313/en/. Accessed: 10th June, 2015.
Acknowledgments
This study was performed as part of the projects No. III43007 and No. III41011, which were founded by the Ministry of Education, Science, and Technological Development of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 2011–2016.
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible editor: Gerhard Lammel
Electronic supplementary material
Below is the link to the electronic supplementary material.
ESM 1
(DOCX 1138 kb)
Rights and permissions
About this article
Cite this article
Stojić, A., Stojić, S.S., Reljin, I. et al. Comprehensive analysis of PM10 in Belgrade urban area on the basis of long-term measurements. Environ Sci Pollut Res 23, 10722–10732 (2016). https://doi.org/10.1007/s11356-016-6266-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-016-6266-4