engleski

Identifying diverse air pollution sources using source apportionment approaches and air quality modelling in a complex urban area

Pinpointing the contribution of sources in complex urban areas, affected by large point sources such as oil refineries, is important for developing emission control strategies. Receptor models based on chemical composition of particulate matter PM), such as Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) are useful means for source apportionment but their results are usually affected by the lack of appropriate inclusion of meteorological parameters that significantly affect the distribution of pollutants in the atmosphere and deserve considerations. This work applies and evaluates different source apportionment techniques to identify the sources of fine particulate matter (PM2.5) and to the less represented – hydrogen sulphide (H2S), ozone (O3), nitrogen dioxide (NO2) and sulphur dioxide (SO2) – in an urban area influenced by a large point source (an oil refinery) in Brod of Bosnia and Herzegovina. Although domestic heating and refinery contributed equally to PM2.5 primary emissions, source apportionment receptor model method based on conditional bivariate probability function (CPBF) revealed that probability ~70% for the PM2.5 concentrations higher than 80th percentile (>37 µg/m3) is assigned to the refinery while ~30% is attributed to the urban sources. The composition of PM2.5 is seen to be dominated by carbonaceous combustion particles, mainly organic carbon (OC), with maximum values appearing during winter. Summer PM2.5 levels were dominated by the sulphate, which can be related to the oil refinery, and ammonium pointing towards the agriculture activities. Urban and highway traffic was the main source (probability ~20%) of NO2 concentrations >80th percentile. Results of multi- pollutant analyses using various source apportionment techniques (i.e. emissions, temporal pollutant variations, chemical PM speciation and CPBF) are ummarized in the form of blame matrix that relates observed concentrations to the sources. An oil refinery was identified as the major source of PM2.5, SO2, H2S and O3 in the area while the city (domestic heating, biomass burning and traffic) is a second contributing source to PM2.5 and SO2 and traffic is the major source of NO2. This work brings an evaluation of source apportionment methods in the assessment of PM and less represented gaseous pollutants NO2, SO2, H2S and O3 that can be used for future scientific applications and assures more efficient air quality management in the analyzed area of Southeastern Europe with prominent air pollution problems.

Blame matrix ; Oil refinery ; Source apportionment ; Bivariate polar plot ; Chemical speciation

nije evidentirano