The Krakow Receptor Modelling Inter-Comparison Exercise

Second to oil, coal is globally the biggest energy source. Coal combustion is utilized mainly for power generation in industry, but in many metropolitan areas in East Europe and Asia also for residential heating in small stoves and boilers. The present investigation, carried out as a case study in a typical major city situated in a European coal combustion region (Krakow, Poland), aims at quantifying the impact on the urban air quality of residential heating by coal combustion in comparison with other potential pollution sources such as power plants, industry and traffic. For that purpose, gaseous emissions (NOx, SO2) were measured for 20 major sources, including small stoves and boilers, and the emissions of particulate matter (PM) was chemically analyzed for 52 individual compounds together with outdoor and indoor PM10 collected during typical winter pollution episodes. The data was analyzed using multivariate receptor modeling yielding source apportionments for PM10, B(a)P and other regulated air pollutants associated with PM10, namely Cd, Ni, As, and Pb. The source apportionment was accomplished using the chemical mass balance modeling (CMB) and constrained positive matrix factorization (CMF) and compared to five other multivariate receptor models (PMF, PCA-MLRA, UNMIX, SOM, CA). The results are potentially very useful for planning abatement strategies in all areas of the world, where coal combustion in small appliances is significant. During the pollution episodes under investigation the PM10 and B(a)P concentrations were up to 8-200times higher than the European limit values. The major culprit for these extreme pollution levels was shown to be residential heating by coal combustion in small stoves and boilers (>50% for PM10 and >90% B(a)P), whereas road transport (<10% for PM10 and <3% for B(a)P), and industry (4-15% for PM10 and <6% for B(a)P) played a lesser role. The indoor PM10 and B(a)P concentrations were not much lower than the outdoor concentrations and were found to have the same sources as outdoor PM10 and B(a)P The inorganic secondary aerosol component of PM10 amounted to around 30%, which may be attributed for a large part to the industrial emission of the precursors SO2 and NOX.JRC.H.4-Transport and air qualit

Self-organizing map algorithm for assessing spatial and temporal patterns of pollutants in environmental compartments: A review

The evaluation of the spatial and temporal distribution of pollutants is a crucial issue to assess the anthropogenic burden on the environment. Numerous chemometric approaches are available for data exploration and they have been applied for environmental health assessment purposes. Among the unsupervised methods, Self-Organizing Map (SOM) is an artificial neural network able to handle non-linear problems that can be used for exploratory data analysis, pattern recognition, and variable relationship assessment. Much more interpretation ability is gained when the SOMbased model is merged with clustering algorithms. This review comprises: (i) a description of the algorithm operation principle with a focus on the key parameters used for the SOM initialization; (ii) a description of the SOM output features and how they can be used for data mining; (iii) a list of available software tools for performing calculations; (iv) an overview of the SOM application for obtaining spatial and temporal pollution patterns in the environmental compartments with focus on model training and result visualization; (v) advice on reporting SOM model details in a pape

Multivariate statistical assessment of polluted soils

Abstract This study deals with the application of several multivariate statistical methods (cluster analysis, principal components analysis, multiple regression on absolute principal components scores) for assessment of soil pollution by heavy metals. The sampling was performed in a heavily polluted region and the chemometric analysis revealed four latent factors, which describe 84.5 % of the total variance of the system, responsible for the data structure. These factors, whose identity was proved also by cluster analysis, were conditionally named “ore specific”, “metal industrial”, “cement industrial”, and “steel production” factors. Further, the contribution of each identified factor to the total pollution of the soil by each metal pollutant in consideration was determined

Receptor Modeling Source Apportionment of PM10 and Benzo(a)pyrene in Krakow, Poland

The main energy source in Krakow, Poland is coal combustion, which is believed to be the reason for frequent winter episodes of extremely high ambient air concentrations of particulate matter (PM10) and associated benzo(a)pyrene B(a)P. Results are presented on the source apportionment of PM10 and B(a)P during two episodes of thermal inversion (14/1 ; 2/3, 2005) at four different air monitoring stations and four apartments (indoor) in the city of Krakow, The results are compared to the Zakopane mountain site selected due to its prominent domestic coal heating and little traffic. The source apportionment was based on receptor modeling of the total of 72 ambient PM samples and 21 individual PM sources, chemically characterised for a high number of organic and inorganic compounds including polyaromatics (15 PAH and 18 azaarenes) heavy metals and trace elements (28 compounds), major ions, soot and organic carbon. An array of multivariate receptor models was used i.e. chemical mass balance (CMB), constrained matrix factorisation (CMF), constrained physical receptor modelling (COPREM) positive matrix factorization (PMF), principle component analysis with multi-linear regression analysis (PCA-MLRA), edge analysis (UNMIX), cluster analysis (CA), and self organizing maps SOM). The variation in the receptor dataset (55 compounds, 60 outdoor and 12 indoor PM samples) allowed the models of the pure factor analysis type (PMF, UNMIX, PCA-MLRA) to identify 3-5 factors of mixed sources. The interpretation of the factors was not straightforward, but pointed to a dominating primary source contribution from coal combustion (>60%) and a minor contribution from traffic (<10%). The secondary PM sources (20-30%) comprised industry and traffic. The results of cluster analysis and self organizing maps supported these indications. PMF was able to disaggregate the coal combustion into three factors i.e. ~10% related to industrial activities, ~20% related to home heating by stoves (coal) and ~30% related to boilers. The chemical fingerprints of the receptor samples and the main PM sources in Krakow and Zakopane allowed the pure chemical mass balance; type model (EPA-CMB8.2) to estimate the major contributions from two primary source types i.e. residential heating by coal combustion in small stoves and low efficiency boilers (~45%) and boilers with rudimentary PM reductions techniques such as cyclones (~15%), one major secondary source deriving from industrial and traffic emissions of SO2 + NOx + possibly HCl (~20%). Five minor primary sources were also identified i.e. traffic 5%, biomass burning ~5%, coke/fuel combustion ~5%, industrial high efficiency coal combustion 3%, and road/salt/rock re-suspension ~2%. The indoor PM10 and B(a)P were found to have the same sources as outdoor PM10 and B(a)P The results obtained by the models CMF and COPREM - which are hybrids of factor analysis and chemical mass balance generally agreed with the CMB results. However, their source contribution estimates are slightly different: residential heating ~30%, boilers with rudimentary PM reductions techniques such as cyclones ~30%, industrial high efficiency coal combustion ~15% traffic 3-7%, secondary 13-21%, road/salt/rock re-suspension 2-8%. All receptor models calculated residential heating to be the principal PM source in Zakopane (70-80%).JRC.H.4-Transport and air qualit

European eels and heavy metals from the Mar Menor lagoon (SE Spain)

the levels of lead (Pb), cadmium (Cd) and mercury (Hg), all known to be harmful heavy metals, in European eels from the Mar Menor lagoon were investigated. On the other hand, the dietary selenium (Se) status is highly related to Hg toxicity (Ralston and Raymond, 2010), and the antagonist effect of Se on Hg is well known since many years ago. The molar ratio Se:Hg may provide an accurate index of risk from fish consumption, and the Selenium Health Benefit Value (HBVSe, Ralston et al., 2016) has been recently considered as a good instrument to better understand of the Se available that remains after its interaction with Hg. Thus, due to the importance of factors affecting public health, information regarding Se concentrations, Se:Hg ratio and the HBVSe were also analysed.Heavy metal pollution is related to the fall in European eel (Anguilla anguilla) populations. The Mar Menor lagoon (SE Spain) is home to an endangered population of this species, which is still caught for human consumption. The presence of Pb, Cd and Hg in the livers and muscles and the Se:Hg ratio in muscle of 150 eels from this lagoon were determined. Pb concentrations were higher than those reported from other populations in the world, while Cd and Hg concentrations in the tissues analysed were lower. In terms of food safety, Se concentrations play an important role in sequestering Hg in eels from this lagoon.This work was supported by “Programa de Apoyo a la InvestigaciónVersión del editor2,35

How to Implement User-Friendly BLMs in the Absence of DOC Monitoring Data: A Case Study on Bulgarian Surface Waters

The metal bioavailability concept is implemented in the Water Framework Directive (WFD) compliance assessment. The bioavailability assessment is usually performed by the application of user-friendly Biotic Ligand Models (BLMs), which require dissolved metal concentrations to be used with the “matching” data of the supporting physicochemical parameters of dissolved organic carbon (DOC), pH and Cadissolved. Many national surface water monitoring networks do not have sufficient matching data records, especially for DOC. In this study, different approaches for dealing with the missing DOC data are presented: substitution using historical data; the appropriate percentile of DOC concentrations; and combinations of the two. The applicability of the three following proposed substitution approaches is verified by comparison with the available matching data: (i) calculations from available TOC data; (ii) the 25th percentile of the joint Bulgarian monitoring network DOC data (measured and calculated by TOC); and (iii) the 25th percentile of the calculated DOC from the matching TOC data for the investigated surface water body (SWB). The application of user-friendly BLMs (BIO-MET, M-BAT and PNEC Pro) to 13 surface water bodies (3 reservoirs and 10 rivers) in the Bulgarian surface waters monitoring network outlines that the suitability of the substitution approaches decreases in order: DOC calculated by TOC &gt; the use of the 25th percentile of the data for respective SWB &gt; the use of the 25th percentile of the Bulgarian monitoring network data. Additionally, BIO-MET is the most appropriate tool for the bioavailability assessment of Cu, Zn and Pb in Bulgarian surface water bodies.</jats:p

How to Implement User-Friendly BLMs in the Absence of DOC Monitoring Data: A Case Study on Bulgarian Surface Waters

The metal bioavailability concept is implemented in the Water Framework Directive (WFD) compliance assessment. The bioavailability assessment is usually performed by the application of user-friendly Biotic Ligand Models (BLMs), which require dissolved metal concentrations to be used with the &ldquo;matching&rdquo; data of the supporting physicochemical parameters of dissolved organic carbon (DOC), pH and Cadissolved. Many national surface water monitoring networks do not have sufficient matching data records, especially for DOC. In this study, different approaches for dealing with the missing DOC data are presented: substitution using historical data; the appropriate percentile of DOC concentrations; and combinations of the two. The applicability of the three following proposed substitution approaches is verified by comparison with the available matching data: (i) calculations from available TOC data; (ii) the 25th percentile of the joint Bulgarian monitoring network DOC data (measured and calculated by TOC); and (iii) the 25th percentile of the calculated DOC from the matching TOC data for the investigated surface water body (SWB). The application of user-friendly BLMs (BIO-MET, M-BAT and PNEC Pro) to 13 surface water bodies (3 reservoirs and 10 rivers) in the Bulgarian surface waters monitoring network outlines that the suitability of the substitution approaches decreases in order: DOC calculated by TOC &gt; the use of the 25th percentile of the data for respective SWB &gt; the use of the 25th percentile of the Bulgarian monitoring network data. Additionally, BIO-MET is the most appropriate tool for the bioavailability assessment of Cu, Zn and Pb in Bulgarian surface water bodies