Disentangling the major source areas for an intense aerosol advection in the Central Mediterranean on the basis of Potential Source Contribution Function modeling of chemical and size distribution measurements

doi:10.1016/j.atmosres.2018.01.011

Atmospheric Research

Volume 204, 15 May 2018, Pages 67-77

https://doi.org/10.1016/j.atmosres.2018.01.011 Get rights and content

Highlights

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Potential Source Contribution Function (PSCF) analysis on hourly aerosol size distribution has been performed.
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PSCF analysis of a rather extensive chemical composition data, have also been obtained, on a daily basis.
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Chemical data include an ample set of metals obtained by Proton Induced X-ray Emission (PIXE), main soluble ions from ionic chromatography and elemental and organic carbon (EC, OC) obtained by thermo-optical measurements.
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The approach allowed to disentangle the major source areas during a complex and fast modulating advection event impacting on the Central Italy in the 2013.
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biomass burning from Eastern Europe and desert dust from Sahara sources have been discriminated based on both chemistry and size distribution time evolution.
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Hourly BT provided the best results in comparison to 6 hours or 24 houri's based calculations.

Abstract

In this paper, we combined a Potential Source Contribution Function (PSCF) analysis of daily chemical aerosol composition data with hourly aerosol size distributions with the aim to disentangle the major source areas during a complex and fast modulating advection event impacting on Central Italy in 2013. Chemical data include an ample set of metals obtained by Proton Induced X-ray Emission (PIXE), main soluble ions from ionic chromatography and elemental and organic carbon (EC, OC) obtained by thermo-optical measurements. Size distributions have been recorded with an optical particle counter for eight calibrated size classes in the 0.27–10 μm range. We demonstrated the usefulness of the approach by the positive identification of two very different source areas impacting during the transport event. In particular, biomass burning from Eastern Europe and desert dust from Sahara sources have been discriminated based on both chemistry and size distribution time evolution. Hourly BT provided the best results in comparison to 6 h or 24 h based calculations.

Graphical Abstract

Introduction

The spatial and temporal variabilities of air quality in the Mediterranean basin is strongly influenced by the climatic patterns and related air masses flows that may transport gas and aerosol pollutants. Depending on the seasonal weather patterns exogenous inputs of pollutants may impact in the Central Mediterranean from Eastern Europe, Western Europe and the African coasts and deserts Traub et al., 2003, Kallos et al., 2007, Pey et al., 2013. Air masses moving along these advection routes may carry pollutants associated with anthropogenic activities and biomass burning fires as well as natural contributions such as desert dust. The EU Air Quality Directive 2008/50/EC allows the Member States to subtract the contribution of natural sources, in particular desert dust, before comparing the ambient concentrations to the relevant limit values. Therefore, estimates of source-receptor relationships is an important and continuously developing task, also for environmental policy. To this aim backward trajectory (BT) analysis has become an extensively used approach for interpretation of gas and aerosol concentration measurements in relation to air mass transport. Although there are many uncertainties associated with trajectory calculations in particular position errors (Stohl, 1998) BTs are considered a handy tool to identify the potential source areas (PSA) of the airborne transported species at the receptor site.

There are many BTs statistical analysis methods which aim at correlating PSA to receptor sites Fleming et al., 2012, Hopke, 2016. Among the most used are the Concentration Field (CF) and the Potential Source Contribution Function (PSCF). Both of them estimate the probability that a given region could contribute to the concentration measured at the site. The popularity of these methods is due also to their availability in Openair module, which is available in the open source programming language R, a popular package specifically designed for data analysis and statistics (R.org, 2013). Openair Carslaw and Ropkins, 2012, Carslaw, 2015 is designed to facilitate atmospheric data analysis. It provides many useful tools to visualize measured data. Besides, it supplies several statistical functions to evaluate model results and performances and to carry out source-receptor correlations studies.

This paper deals with two different atmospheric aerosol types and the related potential source areas that may impact on the Central Mediterranean area, namely biomass burning particles generated from fires in Eastern Europe and mineral dust from the Sahara Desert. Long-range transport of biomass burning plumes has been identified as a significant source of aerosol over Europe and the Mediterranean basin Sciare et al., 2008, Adler et al., 2011, Ancellet et al., 2016. The optical and chemical properties of these air masses are often different from those at the receptor site and may therefore influence the local conditions Ancellet et al., 2016, Moroni et al., 2017. North America (Canada and Alaska) (Markowicz et al., 2016) and Eastern Europe (Damoah et al., 2004) are the source regions that most often impact on Europe in particular in late spring and summertime. Saharan dust advections affect Southern Europe many times during the year (Pey et al., 2013), and their contribution to PM levels often leads to an exceeding of the daily limit values of PM₁₀ in Europe (Nava et al., 2012). Saharan dust advections in the Mediterranean show different transport mechanisms and routes (Barkan et al., 2005), and the air masses' speed and height are also relevant parameter to evaluate. Rural background stations (Querol et al., 2009) are best suited to identify long-range transport (LRT) events and to assess their contribution to the total PM loading.

The case under study is a structured advection impacting Central Italy between April 28 and May 5, 2013. The field campaign has been conducted at the mid-elevation background site of Monte Martano (MM) (Moroni et al., 2015). Detailed study of this event showed a very complex structure in terms of concentration modulation, size distribution and chemical composition. During the event the air quality limit for PM₁₀ has been exceeded for three consecutive days, as recorded at the monitoring stations of the air quality network of Umbria region. In particular, the analysis of the time evolution of the event suggested an impact of biomass burning aerosols first followed by an intense Saharan dust advection.

The primary objective of the present paper is to outline an effective methodology to identify source areas for short intense advections as observed at a receptor site. A part of the work is devoted to comparing the use of CF and PSCF methods, implemented into the opensource package Openair. In spite of the moderate ease of use of this package, due to a few of its limitations as detailed in the paper, we decided to write an on purpose code and to illustrates its implementation to the current problem. More important, we demonstrated the necessity of integrating in the analysis an ample set of chemical and size distribution data to put on a more robust ground the qualitative results obtained by PSCF modeling.

Specifically, the analysis has been based on a full set of chemical speciation data on daily PM₁₀ and PM₂₅ filter samplings and on aerosol size distribution recorded at higher time resolution (1 h) by an optical particle counter. The first goal of the work has been to test the BTs analysis method at different time resolutions in order to understand whether this kind of approach is suitable for characterizing a fast changing and complex advection event on hourly time scales. The second objective has been to demonstrates the use of PSCF model in conjunction with chemical speciation and size distribution data in order to discriminate the PSA in case of mixed events. To these aims, we computed high time resolution (1 h) BTs for this period and applied correlation analysis with chemical and size distribution data both using the Openair package and an original FORTRAN code. A similar approach has been used by Hopke and coworkers (Begum et al., 2005) to describe a forest fire episode in Quebec and exploiting light scattering coefficient, organic carbon (OC), elemental carbon (EC), and sulfate measured at 2-h intervals. These authors applied PSCF with BT calculated every 2 h.

To our knowledge, the present work presents for the first time a PSCF analysis of aerosol size distributions at 1-h resolution. We demonstrated that this choice was relevant to disentangle biomass burning aerosol generated in Eastern Europe from desert dust transported from Sahara sources.

Section snippets

Sampling site

The rural regional background monitoring site of Monte Martano (MM) is located on the ridge of the Martani Mountains chain (1100 m a.s.l., Central Italy, 42° 48′ 19″ N; 12° 33′ 55″ E). Therefore is well suited for the identification and characterization of dust advections and other types of long-range transport in Central Italy. The site has a completely free horizon, is far from local anthropogenic contamination, and lies in the free troposphere for most of the time during the year (Moroni et

BT calculation

Back trajectories were computed running the HYSPLIT code version 4 rev. 513 by Draxler and Rolph (2012), using meteorological fields produced by the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model at a resolution of 1 × 1°.

Using this rather low resolution, the mountain height is probably lower than the true one. Nevertheless, we preferred to use a.g.l. height because, regardless of the particular reference altitude, the model's internal coordinate system

Results and discussion

Between April 24th and May 4th 2013, long-range transported aerosol reached the Monte Martano site determining an increase in PM values of about 60% for PM₁₀ and 42% for PM_2.5, with respect to the mean annual values for 2013 (Table 1). The event is described in detail in Fig. 3: in panel (a) are reported the Dust Optical Depth at 550 nm (DOD550) as calculated by the BSC-DREAM8b model (Basart et al., 2012) together with the number concentrations of particles with diameter larger than 1.6 μ m

Conclusions

In this work, we investigated a complex long-range transport event which impacted on Central Italy in May 2013. We demonstrated that the event was associated with an aerosol transport from two different source areas in a quick temporal succession. On the basis of size distribution and chemical composition analyses, the two events have been identified as a wildfire emission and a Saharan dust advection. The corresponding source areas have been localized in Eastern Europe (Ukraine) and the Sahara

Acknowledgments

We acknowledge the use of data and imagery from LANCE FIRMS operated by the NASA/GSFC/Earth Science Data and Information System (ESDIS) with funding provided by NASA/HQ. We also acknowledge data and images from the WMO SDS-WAS NA-ME-E Regional Center (http://sds-was.aemet.es).

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Citation Excerpt :
Saharan dust particles can be transported over long distances towards Europe (Amato et al., 2016; Barnaba et al., 2017; Cusack et al., 2012) and America (Garrison et al., 2014; Prospero et al., 2005). However, although Saharan dust is recognized as one of the most relevant sources of atmospheric aerosol and bioaerosol on a global scale, the Central Mediterranean is a geographic area profoundly affected by the circulation of air masses of different origin and distinguished by nature, type, quality, and extent of contributions (Cusack et al., 2012; Kallos et al., 2014, 2007; Petroselli et al., 2018a, 2018b). Due to the very different characteristics of the source areas, these air masses are expected to carry different bacterial populations and specific chemical markers and pollutants.
Airborne bacteria were characterized over a 2-y period via high-throughput massive sequencing of 16S rRNA gene in aerosol samples collected at a background mountain European Monitoring and Evaluation Programme (EMEP) Network site (Monte Martano, Italy) located in the Central Mediterranean area. The air mass origin of nineteen samples was identified by air mass modelling and a detailed chemical analysis was performed. Four main origins (Saharan, North-western, North-eastern, and Regional) were identified, and distinct microbial communities were associated with these air masses. Samples featured a great bacterial diversity with Protobacteria being the most abundant phylum, and Sphingomonas followed by Acidovorax, Acinetobacter and Stenotrophomonas the most abundant genera of the dataset. Bacterial genera including potential human and animal pathogens were more abundant in European and in Regional samples compared to Saharan samples; this stressed the relevance of anthropic impact on bacterial populations transported by air masses that cross densely populated areas. The principal aerosol chemical characteristics and the airborne bacterial communities were correlated by cluster analysis, similarity tests and non-metric multidimensional scaling analysis, explaining most of the variability observed. However, the strong correlation between bacterial community structure and air mass origin hampered the possibility to disentangle the effects of variations in bacterial populations and in dust provenance on variations in chemical variables.

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Disentangling the major source areas for an intense aerosol advection in the Central Mediterranean on the basis of Potential Source Contribution Function modeling of chemical and size distribution measurements

Highlights

Abstract

Graphical Abstract

Introduction

Section snippets

Sampling site

BT calculation

Results and discussion

Conclusions

Acknowledgments

Atmos. Environ.

Environ. Model. Softw.

Measurements

Atmos. Environ.

Atmos. Res.

Atmos. Environ.

Atmos. Environ.

Nucl. Inst. Methods Phys. Res. B

J. Aerosol Sci.

Atmos. Environ.

Atmos. Environ.

Atmos. Res.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Atmos. Environ.

Chemical, physical, and optical evolution of biomass burning aerosols: a case study

Atmos. Chem. Phys.