Source Apportionment


European guide on air pollution source apportionment with receptor models.
This report contains a guide and an European harmonised protocol prepared within the framework of the JRC initiative for the harmonisation of source apportionment with reception models.
Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models
In this study, the performance of the source apportionment model applications were evaluated by comparing the model results provided by 44 participants adopting a methodology based on performance indicators: z-scores and RMSE u , with pre-established acceptability criteria. Involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), provided a unique opportunity to cross-validate them. In addition, comparing the modelled source chemical profiles, with those measured directly at the source contributed to corroborate the chemical profile of the tested model results. The most used RM was EPA- PMF5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) and more difficulties are observed with SCE time series (72% of RMSE u accepted). Industry resulted the most problematic source for RMs due to the high variability among participants. Also the results obtained with CTMs were quite comparable to their ensemble reference using all models for the overall average (>92% of successful z-scores) while the comparability of the time series is more problematic (between 58% and 77% of the candidates’ RMSE u are accepted). In the CTM models a gap was observed between the sum of source contributions and the gravimetric PM 10 mass likely due to PM underestimation in the base case. Interestingly, when only the tagged species CTM results were used in the reference, the differences between the two CTM approaches (brute force and tagged species) were evident. In this case the percentage of candidates passing the z-score and RMSE u tests were only 50% and 86%, respectively. CTMs showed good comparability with RMs for the overall dataset (83% of the z-scores accepted), more differences were observed when dealing with the time series of the single source categories. In this case the share of successful RMSE u was in the range 25% - 34%.
Air quality in the Danube macro-region - Towards a coordinated science-based approach in support of policy development
Air quality in the Danube macro-region is a serious problem. Exceedances of PM 10 and precursor gases, NO 2 or SO 2 , have led to infringement procedures in almost all of the EU-Danube Member States and some of them have been referred to court.
The Danube macro-region encompasses one of Europe’s air pollution “hot spots” where the development of a strategy to achieve the standards laid down in EU legislation requires appropriate diagnosis with the most suitable tools.
Several pilot urban areas in EU Member States, representing different situations within this macro-region, were chosen as a case study. A detailed analysis of the causes of pollution in eight cities (Zagreb, Budapest, Sofia, Vienna, Bucharest, Munich, Prague and Bratislava) was then used to identify measures to counter the exceedances of limit values (Directives 2008/50/EC and 2004/107/EC) and to comply with national emission ceiling (NEC) obligations (Directive 2016/2284/EU).
A comparative analysis of the causes of air pollution in three cities of the Danube region
A set of pilot urban areas, representing different situations within the Danube region, was chosen as case study. The detailed analysis of the causes of pollution in the three studied cities (Zagreb, Budapest and Sofia) was then used to propose measures to be implemented in the air quality plans that local, regional and national authorities are requested to put in place to face the exceedances of limit values (Directives 2008/50/EC and 2004/107/EC) and to comply with the national emission ceilings (NEC) obligations (Directive 2001/81/EC).
The picture resulting from this study highlights the complexity of the pollution processes and the need to adopt flexible and multilevel measures to deal with them. Most of the pollutants are emitted locally. However, the medium to long range transport may be also considerable depending on the season and the meteorological conditions. For that reason, there is a need for action at local, national and international scales. The success of the measures mostly depends on the coordination among different levels taking into account the needs/inputs from the relevant sectorial policies.
Review and gaps identification in Air Quality and Health Assessment methodologies at regional and local scale
The methodologies used in Europe to identify the sources of atmospheric pollutants are summarized and discussed. The report combines information available from surveys and scientific reviews on source apportionment models available in the literature and the results of the questionnaire carried out within the framework of the project APPRAISAL.
The European Intercomparison Exercise for Receptor Models 2011-2012 - PART I
In order to have a better understanding about the comparability and performance of different source apportionment methodologies an intercomparison exercise (IE) has been organized by the European Commission’s Joint Research Centre (JRC). This IE is part of a JRC initiative for the harmonization of source apportionment with receptor models.
The Krakow receptor modelling inter-comparison exercise
In order to offer policy makers an adequate support to the development of appropriate emission reduction strategies, the Joint Research Centre (JRC) of the European Commission in collaboration with relevant scientific partners has embarked on integrated studies in heavily polluted areas for the assessment of emission sources impact on air pollution, and human exposure/health.
DeltaSA tool for source apportionment benchmarking, description and sensitivity analysis
DeltaSA is an R-package and a Java on-line tool developed at the EC-Joint Research Centre to assist and benchmark source apportionment applications. Its key functionalities support two critical tasks in this kind of studies: the assignment of a factor to a source in factor analytical models (source identification) and the model performance evaluation. The source identification is based on the similarity between a given factor and source chemical profiles from public databases. The model performance evaluation is based on statistical indicators used to compare model output with reference values generated in intercomparison exercises. The references values are calculated as the ensemble average of the results reported by participants that have passed a set of testing criteria based on chemical profiles and time series similarity. In this study, a sensitivity analysis of the model performance criteria is accomplished using the results of a synthetic dataset where “a priori” references are available. The consensus modulated standard deviation punc gives the best choice for the model performance evaluation when a conservative approach is adopted.
On the validity of the incremental approach to estimate the impact of cities on air quality
The question of how much cities are the sources of their own air pollution is not only theoretical as it is critical to the design of effective strategies for urban air quality planning. In this work, we assess the validity of the commonly used incremental approach to estimate the likely impact of cities on their air pollution. With the incremental approach, the city impact (i.e. the concentration change generated by the city emissions) is estimated as the concentration difference between a rural background and an urban background location, also known as the urban increment. We show that the city impact is in reality made up of the urban increment and two additional components and consequently two assumptions need to be fulfilled for the urban increment to berepresentative of the urban impact. The first assumption is that the rural background location is not influenced by emissions from within the city whereas the second requires that background concentration levels, obtained with zero city emissions, are equal at both locations. Because the urban impact is not measurable, the SHERPA modelling approach, based on a full air quality modelling system, is used in this work to assess the validity of these assumptions for some European cities. Results indicate that for PM 2.5, these two assumptions are far from being fulfilled for many large or medium city sizes. For this type of cities, urban increments are largely underestimating city impacts. Although results are in better agreement for NO2, similar issues are met. In many situations the incremental approach is therefore not an adequate estimate of the urban impact on air pollution. This poses issues in terms of interpretation when these increments are used to define strategic options in terms of air quality planning. We finally illustrate the interest of comparing modelled and measured increments to improve our confidence in the model results.
Sources and geographic origin of particulate matter in urban areas of the Danube macro-region: The cases of Zagreb (Croatia), Budapest (Hungary) and Sofia (Bulgaria)
The contribution of main PM pollution sources and their geographic origin in three urban sites of the Danube macro-region (Zagreb, Budapest and Sofia) were determined by combining receptor and Lagrangian models. The source contribution estimates were obtained with the Positive Matrix Factorization (PMF) receptor model and the results were further examined using local wind data and backward trajectories obtained with FLEXPART. Potential Source Contribution Function (PSCF) analysis was applied to identify the geographical source areas for the PM sources subject to long-range transport. Gas-to-particle transformation processes and primary emissions from biomass burning are the most important contributors to PM in the studied sites followed by re-suspension of soil (crustal material) and traffic. These four sources can be considered typical of the Danube macro-region because they were identified in all the studied locations. Long-range transport was observed of: a) sulphateenriched aged aerosols, deriving from SO2 emissions in combustion processes in the Balkans and Eastern Europe and b) dust from the Saharan and Karakum deserts. The study highlights that PM pollution in the studied urban
Source apportionment and sensitivity analysis: two methodologies with two different purposes
This work reviews the existing methodologies for source apportionment and sensitivity analysis to identify key differences and stress their implicit limitations. The emphasis is laid on the differences between source “impacts” (sen- sitivity analysis) and “contributions” (source apportionment) obtained by using four different methodologies: brute-force top-down, brute-force bottom-up, tagged species and decoupled direct method (DDM). A simple theoretical example to compare these approaches is used highlighting differences and potential implications for policy. When the relationships between concentration and emissions are linear, impacts and contributions are equivalent concepts. In this case, source ap- portionment and sensitivity analysis may be used indifferently for both air quality planning purposes and quantifying source contributions. However, this study demonstrates that when the relationship between emissions and concentrations is nonlinear, sen- sitivity approaches are not suitable to retrieve source contributions and source apportionment methods are not appropri- ate to evaluate the impact of abatement strategies. A quantification of the potential nonlinearities should therefore be the first step prior to source apportionment or planning applications, to prevent any limitations in their use. When nonlin- earity is mild, these limitations may, however, be acceptable in the context of the other uncertainties inherent to complex models. Moreover, when using sensitivity analysis for planning, it is important to note that, under nonlinear circumstances, the calculated impacts will only provide information for the exact conditions (e.g. emission reduction share) that are simulated.
A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises
Source Apportionment (SA) is the practice of deriving information about the pollution sources and the amount they contribute to measured concentrations. Receptor models (RMs) apportion the measured mass of pollutants to its emission sources by using multivariate analysis to solve a mass balance equation (Friedlander,1973; Schauer et al., 1996; Thurston and Spengler, 1985). RMs derive information from measurements including estimations of their uncertainty and have been extensively used in Europe to estimate the contribution of emission sources to atmospheric pollution at a given site or area (Belis et al., 2013; Viana et al., 2008a).
In the Chemical Mass Balance (CMB) approach, both chemical concentrations of pollutants, including their uncertainties, and chemical fingerprints of the sources (source profiles) are used as input. Inthe multivariate factor analytical approach (MFA), only environmental concentrations and uncertainties of pollutants are used as input data and the model computes the factor profiles and the mass contributed by the factors. The CMB approach is sensitive to the selection of sources, their stability and the collinearity among them. Differences between the methods used to analyse the source and ambient samples may also impact the results. On the other hand, MFA models identify factors that have to be attributed to emission sources. For a more thorough discussion about the pros and cons of the two approaches see Hopke (2010), Watson et al. (2008) and Belis et al. (2013).
Previous studies provided first estimates of the output variability by comparing the results of different RMs on the same dataset (Hopke et al., 2006; Larsen et al., 2008; Favez et al., 2010; Viana et al., 2008b; Pandolfi et al., 2008). In the present work, carried out in the frame of FAIRMODE (Forum for Air Quality Modelling), intercomparison exercises aimed at quantitatively assessing the performance and the uncertainty of RMs by comparing the results reported from different practitioners on the same dataset using different RM techniques.
SPECIEUROPE: The European data base for PM source profiles
A new database of atmospheric particulate matter emission source profiles in Europe (SPECIEUROPE) developed in the framework of the Forum for air quality modeling in Europe (FAIRMODE, Working Group 3) is accessible at the website. It contains the chemical composition of particulate matter emission sources reported in the scientific literature and reports drafted by competent authorities. The first release of SPECIEUROPE consists of 151 measured (original), 13 composite (merging different subcategories of similar sources), 6 calculated (from stoichiometric composition) and 39 derived (results of source apportionment studies) profiles. Each profile is related to one or more source categories or subcategories. The sources with the highest PM relative mass toxic pollutants such as PAHs are fuel oil burning, ship emissions, coke burning and wood burning. Heavy metals are most abundant in metal processing activities while halogens are mostly present in fertilizer production, coal burning and metallurgic sector. Anhydrosugars are only measured in biomass and wood burning source categories, because are markers for these categories. The alkaline earth metals are mostly present in road dust, cement production, soil dust and sometimes coal burning. Source categories like traffic and industrial, which contain heterogeneous subcategories, show the greatest internal variability.
The relationships between sources profiles were also explored using a cluster analysis approach based upon the Standardized Identity Distance (SID) indicator. The majority of profiles are allocated in 8 major clusters. Some of the clusters include profiles mainly from one source category (e.g. wood burning) while others, such as industrial source profiles, are more heterogeneous and spread over three different clusters.
A new methodology to assess the performance and uncertainty of source apportionment models in intercomparison exercises
A new methodology to assess source apportionment model performance in intercomparison exercises, encompassing the preparation of real-world and synthetic datasets and the evaluation of the source apportionment results reported by participants, is described. The evaluation consists of three types of tests: complementary tests, preliminary tests, and performance tests. The complementary tests provide summary information about the source apportionment results as a whole. The preliminary tests check whether source/factors belong to a given source category. Three types of indicators: Pearson correlation (Pearson), standardized identity distance (SID), and weighted difference (WD) are used to test factor/ source chemical profiles, while factor/source time series and contribution-to-species values are tested only using the Pearson. The performance tests, based on international standards for proficiency testing, are targeted at evaluating whether the reported biases in the quantification of the factor/source contribution estimates (SCEs) and uncertainties are consistent with previously established quality standards in a fitness-for-purpose approach. Moreover, the consistency of the SCE time series is evalu- ated using a variant of the RMSE normalised by the reference standard uncertainty.
The described methodology facilitates a thorough evaluation of the source apportionment output. The new indicator to compare source or factor profiles presented in this study (SID) is more robust and provides additional information compared to the existing ones.
Contributions to cities' ambient particulate matter (PM): A systematic review of local source contributions at global level
For reducing health impacts from air pollution, it is important to know the sources contributing to human exposure. This study systematically reviewed and analysed available source apportionment studies on particulate matter (of diameter of 10 and 2.5 microns, PM10 and PM2.5) performed in cities to estimate typical shares of the sources of pollution by country and by region. A database with city source apportionment records, estimated with the use of receptor models, was also developed and available at the website of the World Health Organization.
A total of 419 source apportionment records from studies conducted in cities of 51 countries were used to calculate regional averages of sources of ambient particulate matter. Based on the available infor- mation, globally 25% of urban ambient air pollution from PM2.5 is contributed by traffic, 15% by industrial activities, 20% by domestic fuel burning, 22% from unspecified sources of human origin, and 18% from natural dust and salt. The available source apportionment records exhibit, however, important hetero- geneities in assessed source categories and incompleteness in certain countries/regions.
Enhancing source apportionment with receptor models to foster the air quality directive implementation
Receptor models (RMs) identify pollution sources by solving a mass balance equation using measured chemical composition of samples either in combination with known source profiles or not. This approach has been extensively used in North America and South-Eastern Asia mainly on particulate matter (PM). Also, in Europe RMs found wide acceptance and contributed to the identification of sources in support of remediation measures development. With the aim of harmonising the activity on receptor modelling in Europe and supporting the implementation of Directive 2008/50/EC, a survey on the use of this methodology was carried out. In this study we discuss the sources of uncertainty in the input data, and the uncertainty contribution deriving from critical steps. We describe a methodology to assess RMs performance in intercomparison exercises developed and evaluated by the JRC within the framework of the forum for air quality modelling (FAIRMODE).
Current trends in the use of models for source apportionment of air pollutants in Europe
Forum for Air Quality Modelling in Europe (FAIRMODE) sub-group 2 (SG2) on the ‘Contribution of natural sources and source apportionment’ has been formed in response to the need for a harmonised European approach in the use of models for source apportionment, addressing the requirements of the current Air Quality Directive 2008/50/EU. Within SG2, a review was performed on source apportionment modelling methods used by member states for the preparation of their extension reports regarding compliance with PM 10 limit values. This review was extended to identify the modelling source apportionment methodologies used by member states for various pollutants. The extended study was performed by directly addressing a questionnaire to the national representatives of 38 countries of the European region and to 50 national experts. The responses revealed the widespread use of both receptor and dispersion models but also demonstrated a number of issues related to the validation of the source apportionment methodology applied.
Critical review and meta-analysis of ambient particulate matter source apportionment using receptor models in Europe
A review was conducted of the published literature on source apportionment of ambient particulate matter (PM) in Europe using receptor models (RMs). Consistent records were identified for source contribution estimates of PM mass concentrations for 272 records and of organic carbon (OC) in PM for 60 records. Over the period 2000-2012, a shift was observed in the use of RMs from principal component analysis, enrichment factors, and classical factor analysis to Positive Matrix Factorization while Chemical Mass Balance is still topical.
Following a meta-analysis of the published results, six major source categories for PM were defined that comprise almost all individual sources apportioned in Europe: atmospheric formation of secondary inorganic aerosol (SIA), traffic, re-suspension of crustal/mineral dust, biomass burning, (industrial) point sources, and sea/road salt. For the OC fraction, the three main source categories were: atmospheric formation of secondary organic aerosol, biomass burning, and fossil fuel combustion. The geographical and seasonal variations of these sources are mapped and discussed.
A special analysis of PM concentrations that exceed the current European air quality limits indicated SIA and traffic as the most important source categories to target for abatement throughout the year together with biomass burning during the cold season.